Tootfinder

Correcting sample selection bias with categorical outcomes
Onil Boussim
https://arxiv.org/abs/2510.05551 https://arxiv.org/pdf/2510.05551

Correcting sample selection bias with categorical outcomes
In this paper, we propose a method for correcting sample selection bias when the outcome of interest is categorical, such as occupational choice, health status, or field of study. Classical approaches to sample selection rely on strong parametric distributional assumptions, which may be restrictive in practice. While the recent framework of Chernozhukov et al. (2023) offers a nonparametric identification using a local Gaussian representation (LGR) that holds for any bivariate joint distribution…

Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs
Xueyan Li, Guinan Su, Mrinmaya Sachan, Jonas Geiping
https://arxiv.org/abs/2510.05987 https://

Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs
Large Language Models (LLMs) are increasingly applied to complex tasks that require extended reasoning. In such settings, models often benefit from diverse chains-of-thought to arrive at multiple candidate solutions. This requires two competing objectives: to inject enough stochasticity to explore multiple reasoning chains, and to ensure sufficient accuracy and quality in each path. Existing works pursue the first objective by increasing exploration at highly uncertain steps with higher tempera…

A new composite Mann-Whitney test for two-sample survival comparisons with right-censored data
Abid Hussain, Touqeer Ahmad
https://arxiv.org/abs/2510.05353 https://

A new composite Mann-Whitney test for two-sample survival comparisons with right-censored data
A fundamental challenge in comparing two survival distributions with right censored data is the selection of an appropriate nonparametric test, as the power of standard tests like the Log rank and Wilcoxon is highly dependent on the often unknown nature of the alternative hypothesis. This paper introduces a new, distribution free two sample test designed to overcome this limitation. The proposed method is based on a strategic decomposition of the data into uncensored and censored subsets, from …

A Sample of HeII {\lambda}4686 "Changing-Look" Quasars
Wentao Lu, Jun-Xian Wang
https://arxiv.org/abs/2510.06753 https://arxiv.org/pdf/2510.06753…

A Sample of HeII λ4686 "Changing-Look" Quasars
We present the first systematic search for "changing-look" ("CL") behavior in the broad He ii λ4686 emission line in quasars, utilizing repeated spectroscopy from the Sloan Digital Sky Survey (SDSS). The He ii line, originating from high-ionization gas and powered by extreme ultraviolet photons, serves as a sensitive tracer of changes in the ionizing continuum. After applying strict spectral selection criteria and visual inspection to a parent sample of over 9,000 quasars with multi-epoch spec…

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

Sample complexity for entropic optimal transport with radial cost
Ruiyu Han. Johannes Wiesel
https://arxiv.org/abs/2510.05685 https://arxiv.org/pdf/2510.05…

Sample complexity for entropic optimal transport with radial cost
We prove a new sample complexity result for entropy regularized optimal transport. Our bound holds for probability measures on $\mathbb R^d$ with exponential tail decay and for radial cost functions that satisfy a local Lipschitz condition. It is sharp up to logarithmic factors, and captures the intrinsic dimension of the marginal distributions through a generalized covering number of their supports. Examples that fit into our framework include subexponential and subgaussian distributions and r…

Spectral Thresholds for Identifiability and Stability:Finite-Sample Phase Transitions in High-Dimensional Learning
William Hao-Cheng Huang
https://arxiv.org/abs/2510.03809 https…

Spectral Thresholds for Identifiability and Stability:Finite-Sample Phase Transitions in High-Dimensional Learning
In high-dimensional learning, models remain stable until they collapse abruptly once the sample size falls below a critical level. This instability is not algorithm-specific but a geometric mechanism: when the weakest Fisher eigendirection falls beneath sample-level fluctuations, identifiability fails. Our Fisher Threshold Theorem formalizes this by proving that stability requires the minimal Fisher eigenvalue to exceed an explicit $O(\sqrt{d/n})$ bound. Unlike prior asymptotic or model-specifi…

Sample-Efficient and Smooth Cross-Entropy Method Model Predictive Control Using Deterministic Samples
Markus Walker, Daniel Frisch, Uwe D. Hanebeck
https://arxiv.org/abs/2510.05706

Sample-Efficient and Smooth Cross-Entropy Method Model Predictive Control Using Deterministic Samples
Cross-entropy method model predictive control (CEM--MPC) is a powerful gradient-free technique for nonlinear optimal control, but its performance is often limited by the reliance on random sampling. This conventional approach can lead to inefficient exploration of the solution space and non-smooth control inputs, requiring a large number of samples to achieve satisfactory results. To address these limitations, we propose deterministic sampling CEM (dsCEM), a novel framework that replaces the ra…

Back to delayering the PIC12F683. I have a ton of imagery and could do some narrated analysis already but my throat is still sore from being sick so I don't want to be recording any audio.
This is after another three minutes in room temperature Whink. I got a fresh squirt of acid in case the old stuff was getting reacted away but I don't think there is enough glass in this sample to meaningfully dilute it.

I have decided that tomorrow morning I really have to, um, get my rear in gear and get two things done:
1) check company accounts for submission
2) bowel cancer test sample fun
This is my glamorous life!

The Gamma-ray Luminosity Function of Flat-Spectrum Radio Quasars
Garima Rajguru, Lea Marcotulli, Marco Ajello, Mattia Di Mauro, Meg Urry
https://arxiv.org/abs/2510.05515 https:/…

The Gamma-ray Luminosity Function of Flat-Spectrum Radio Quasars
We have utilized the largest sample of $γ$-ray selected Fermi flat-spectrum radio quasars (FSRQs) ever used (519 sources) to construct the luminosity function and its evolution through the cosmic history. In addition to spanning large redshift ($0

Thermodynamics of data
Borko Stosic
https://arxiv.org/abs/2510.06818 https://arxiv.org/pdf/2510.06818

Thermodynamics of data
The recently introduced concept of generalized thermodynamics is explored here in the context of 1d, 2d and 3d data analysis, performed on samples drawn from a 3d X-ray soil sample image. Different threshold levels are used to binarize the 3d sample, wherefrom relative frequencies of binary patterns are found and then used to address finite size scaling behavior of the response functions as a function of the disorder parameter (equivalent of temperature in thermodynamics). It is found that for …

Series B, Episode 07 - Killer
BELLFRIAR: Embalming fluid, as near as dammit.
BLAKE: Mm? What?
BELLFRIAR: The blood sample Wiler took, these are the lab results coming through.
https://blake.torpidity.net/m/207/413 B7B4

Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models
Raha Askari, Sina Zarrie{\ss}, \"Ozge Alacam, Judith Sieker
https://arxiv.org/abs/2510.04764

Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models
Implicit meanings are integral to human communication, making it essential for language models to be capable of identifying and interpreting them. Grice (1975) proposed a set of conversational maxims that guide cooperative dialogue, noting that speakers may deliberately violate these principles to express meanings beyond literal words, and that listeners, in turn, recognize such violations to draw pragmatic inferences. Building on Surian et al. (1996)'s study of children's sensitivity to viol…

Efficient tensor-network simulations of weakly-measured quantum circuits
Darren Pereira, Leonardo Banchi
https://arxiv.org/abs/2510.07211 https://arxiv.org…

Efficient tensor-network simulations of weakly-measured quantum circuits
We present a tensor-network-based method for simulating a weakly-measured quantum circuit. In particular, we use a Markov chain to efficiently sample measurements and contract the tensor network, propagating their effect forward along the spatial direction. Applications of our algorithm include validating quantum computers (capable of mid-circuit measurements) in regimes of easy classical simulability, and studying generative-machine-learning applications, where sampling from complex stochastic…

Oracle-Guided Masked Contrastive Reinforcement Learning for Visuomotor Policies
Yuhang Zhang, Jiaping Xiao, Chao Yan, Mir Feroskhan
https://arxiv.org/abs/2510.05692 https://

Oracle-Guided Masked Contrastive Reinforcement Learning for Visuomotor Policies
A prevailing approach for learning visuomotor policies is to employ reinforcement learning to map high-dimensional visual observations directly to action commands. However, the combination of high-dimensional visual inputs and agile maneuver outputs leads to long-standing challenges, including low sample efficiency and significant sim-to-real gaps. To address these issues, we propose Oracle-Guided Masked Contrastive Reinforcement Learning (OMC-RL), a novel framework designed to improve the samp…

Characterizing the variability of a sample of massive stars in eclipsing binaries
C. I. Eze (Nicolaus Copernicus Astronomical Center, Warsaw, Poland, Department of Physics and Astronomy, University of Nigeria, Nsukka, Nigeria), G. Handler (Nicolaus Copernicus Astronomical Center, Warsaw, Poland), F. Kahraman Ali\c{c}avu\c{s} (\c{C}anakkale Onsekiz Mart University, Faculty of Sciences, Physics Department, \c{C}anakkale, T\"urkiye), T. Pawar (Nicolaus Copernicus Astronomical Center,…

Characterizing the variability of a sample of massive stars in eclipsing binaries
Massive stars exhibit a perplexing mismatch between their inferred masses from different observational techniques, posing a significant challenge to our understanding of stellar evolution and structure. This discrepancy is believed to be caused by the underestimation of the convective core masses. The efficiency of such measurement is usually impaired by a lot of processes at work in the interior of the stars such as convective core overshooting and interior rotation. By integrating the precisi…

Optimal Zeroth-Order Bilevel Optimization
Alireza Aghasi, Jeongyeol Kwon, Saeed Ghadimi
https://arxiv.org/abs/2510.03646 https://arxiv.org/pdf/2510.03646…

Optimal Zeroth-Order Bilevel Optimization
In this paper, we develop zeroth-order algorithms with provably (nearly) optimal sample complexity for stochastic bilevel optimization, where only noisy function evaluations are available. We propose two distinct algorithms: the first is inspired by Jacobian/Hessian-based approaches, and the second builds on using a penalty function reformulation. The Jacobian/Hessian-based method achieves a sample complexity of $\mathcal{O}(d^3/ε^2)$, which is optimal in terms of accuracy $ε$, albeit with po…

Adapting HFMCA to Graph Data: Self-Supervised Learning for Generalizable fMRI Representations
Jakub Frac, Alexander Schmatz, Qiang Li, Guido Van Wingen, Shujian Yu
https://arxiv.org/abs/2510.05177

Adapting HFMCA to Graph Data: Self-Supervised Learning for Generalizable fMRI Representations
Functional magnetic resonance imaging (fMRI) analysis faces significant challenges due to limited dataset sizes and domain variability between studies. Traditional self-supervised learning methods inspired by computer vision often rely on positive and negative sample pairs, which can be problematic for neuroimaging data where defining appropriate contrasts is non-trivial. We propose adapting a recently developed Hierarchical Functional Maximal Correlation Algorithm (HFMCA) to graph-structured f…

Thank you #rhel

After sssd upgrade, useradd and usermod fail to flush the sssd cache with "DB version too old for domain implicit_files!". - Red Hat Customer Portal
After sssd upgrade, useradd and usermod fail to flush the sssd cache with "DB version too old for domain implicit_files!". Sample reproducer: # useradd testuser0 # systemctl is-enabled sssd.service # systemctl disable sssd.service # systemctl stop sssd.service # yum update sssd Sample outputs of a sssd upgrade system from sssd-2.3.0-9.el8(RHEL8.3) to sssd-2.5.2-2.el8(RHEL8.5): # useradd testuser1 [sss_cache] [sysdb_domain_cache_connect] (0x0010): DB version too old [0.22], expected [0.23] for d…

The impact of missing data on the construction of LISA Time Delay Interferometry Michelson variables
Ollie Burke, Martina Muratore, Graham Woan
https://arxiv.org/abs/2510.06406 …

The impact of missing data on the construction of LISA Time Delay Interferometry Michelson variables
We investigate the impact of missing input data on the construction of second-generation Time Delay Interferometry (TDI) variables, which enable data analysis for the Laser Interferometer Space Antenna (LISA). TDI relies on the introduction of precise time delays into the raw interferometric data streams before they are combined to suppress otherwise dominant laser phase noise. We show that a single missing sample, corresponding to 0.25 s of data, will result in an effective data gap of approxi…

Greedy Thiele continued-fraction approximation on continuum domains in the complex plane
Tobin A. Driscoll, Yuxing Zhou
https://arxiv.org/abs/2510.07295 https://

Greedy Thiele continued-fraction approximation on continuum domains in the complex plane
We describe an adaptive greedy algorithm for Thiele continued-fraction approximation of a function defined on a continuum domain in the complex plane. The algorithm iteratively selects interpolation nodes from an adaptively refined set of sample points on the domain boundary. We also present new algorithms for evaluating Thiele continued fractions and their accessory weights using only a single floating-point division. Numerical experiments comparing the greedy TCF method with the AAA algorithm…

The award for the pull request of the day goes to OpenSSH:
https://github.com/openssh/openssh-portable/pull/554

Make 3rd party unit tests log "PERKELE" instead of "FUCKOFF" by martinpaljak · Pull Request #554 · openssh/openssh-portable
I'm using this sample file as input to known_hosts parsing unit tests. I don't mind a bit of swearing but this Finnish word is a bit less direct than "FUCKOFF". Reference: https:/...

A Comparison of Star Formation Rates by Different Tracers in Nearby Galaxies
Huynh Anh N. Le, Jong-Hak Woo, Yongquan Xue, Ashraf Ayubinia, Changseok Kim, Xiaozhi Lin
https://arxiv.org/abs/2510.05687

A Comparison of Star Formation Rates by Different Tracers in Nearby Galaxies
We utilize a large sample of $\sim$113,000 galaxies ($z < 0.3$) from the Sloan Digital Sky Survey with high-quality data to compare star formation rates (SFRs) across multiple diagnostic methods and examine their connection to Active Galactic Nuclei (AGNs) strength, indicated by Eddington ratio. Our sample encompassed star-forming (SF), composite, Seyfert, and LINER galaxies. Our analysis utilizes various SFRs indicators, including observed infrared flux ($\rm SFR_{FIR}$) from AKARI/Herschel ($…

First Measurement of the $D_s^ \rightarrow K^0\mu^ \nu_{\mu}$ Decay
BESIII Collaboration, et al.
https://arxiv.org/abs/2510.05904 https://arxiv.org/pdf/251…

First Measurement of the $D_s^+\rightarrow K^0μ^+ν_μ$ Decay
We report the first measurement of the semileptonic decay $D^+_s \rightarrow K^0μ^+ν_μ$, using a sample of $e^+e^-$ annihilation data corresponding to an integrated luminosity of $7.33~\mathrm{fb}^{-1}$ collected at center-of-mass energies between 4.128 to 4.226~GeV with the BESIII detector at the BEPCII collider. The branching fraction of the decay is measured to be $\mathcal{B}(D^+_s\rightarrow K^0μ^+ν_μ) = (2.89 \pm 0.27_{\rm stat} \pm 0.12_{\rm syst})\times 10^{-3}$, where the first u…

The First Dedicated Survey of Atmospheric Escape from Planets Orbiting F Stars
Morgan Saidel, Shreyas Vissapragada, Heather Knutson, Ethan Schreyer, Mike Greklek-McKeon, Jonathan Gomez Barrientos, W. Garrett Levine, Carlos Gasc\'on, Morgan MacLeod, Haedam Im, Nick Tusay
https://arxiv.org/abs/2510.05240

The First Dedicated Survey of Atmospheric Escape from Planets Orbiting F Stars
Hydrodynamic escape can strip the envelopes of close-in exoplanets, but most observations of atmospheric mass loss to date have been confined to planets orbiting K and M dwarfs. A growing body of detections of atmospheric escape from planets orbiting early-type stars indicates that they may have significantly stronger and more extended outflows than planets orbiting cooler stars. However, it is unclear whether this limited sample of planets is representative of all gas giants orbiting early-typ…

Quantum Lattice Boltzmann Method for Multiple Time Steps Without Reinitialization for Linear Advection-Diffusion Problems
Aaron Nagel, Johannes L\"owe
https://arxiv.org/abs/2510.05965

Quantum Lattice Boltzmann Method for Multiple Time Steps Without Reinitialization for Linear Advection-Diffusion Problems
To simulate highly-resolved flow fields, we extend the Quantum Lattice Boltzmann Method (QLBM) to be able to simulate multiple time steps without state extraction or reinitialization. We adjust and extend given QLBM approaches from the literature to completely remove the need to measure or reinitialize the flow field in between the simulation time steps. Therefore, our algorithm does not require to sample the entire flow field at any time. We solve the linear advection-diffusion problem and der…

Multi-NA Metalens Array for Compact High-NA Microscopy
Alireza Khalilian, Jie Fan, Mehdi Sh. Yeganeh, Joe Lo, Yasha Yi
https://arxiv.org/abs/2510.07123 https://

Multi-NA Metalens Array for Compact High-NA Microscopy
We demonstrate a CMOS-compatible silicon-rich nitride metalens array for visible microscopy at 660 nm. Three co-planar elements provide numerical apertures of 0.54, 0.92, and 0.97, enabling within-sample NA benchmarking without objective swaps. Imaging of annular cell monolayers labeled in the AF647 ZO-1 channel shows progressive sharpening of junctional edges and reduced blur with increasing NA, consistent with diffraction-limited scaling. The compact, planar platform supports direct integrati…

Strong progenitor age bias in supernova #cosmology – I. Robust and ubiquitous evidence from a larger sample of host galaxies in a broader redshift range / II. Alignment with DESI BAO and signs of a non-accelerating universe: https://academic.oup.com/mnras/article/538/4/3340/8098234 / https://academic.oup.com/mnras/article/544/1/975/8281988 -> Universe's expansion 'is now slowing, not speeding up': https://ras.ac.uk/news-and-press/research-highlights/universes-expansion-now-slowing-not-speeding (this has been claimed by the group since at least 2023 - http://vietnam.in2p3.fr/2023/windows/transparencies/02_tuesday/Astro_5/01_Son.pdf - and is rejected by the SN cosmology community as https://bsky.app/profile/astromarc.bsky.social/post/3m4xmikwfds26 explains).

Testing the equality of estimable parameters across many populations
Marcos Romero-Madro\~nal, Mar\'ia de los Remedios Sillero-Denamiel, Mar\'ia Dolores Jim\'enez-Gamero
https://arxiv.org/abs/2510.06763

Testing the equality of estimable parameters across many populations
The comparison of a parameter in $k$ populations is a classical problem in statistics. Testing for the equality of means or variances are typical examples. Most procedures designed to deal with this problem assume that $k$ is fixed and that samples with increasing sample sizes are available from each population. This paper introduces and studies a test for the comparison of an estimable parameter across $k$ populations, when $k$ is large and the sample sizes from each population are small when …

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[8/13]:
- Improved Sample Complexity For Diffusion Model Training Without Empirical Risk Minimizer Access
Mudit Gaur, Prashant Trivedi, Sasidhar Kunapuli, Amrit Singh Bedi, Vaneet Aggarwal

🇺🇦 #NowPlaying on #BBC6Music's #TheCraigCharlesFunkAndSoulShow
Bobby Womack:
🎵 If You Think You're Lonely Now
#BobbyWomack
https://catfood88.bandcamp.com/track/bobby-womack-if-you-think-youre-lonely-now-high-pitch-sample-chop-remix
https://open.spotify.com/track/6BSHpKBd2pc3A9WQfRWzyM

From Learning to Mastery: Achieving Safe and Efficient Real-World Autonomous Driving with Human-In-The-Loop Reinforcement Learning
Li Zeqiao, Wang Yijing, Wang Haoyu, Li Zheng, Li Peng, Liu Wenfei, Zuo Zhiqiang
https://arxiv.org/abs/2510.06038

From Learning to Mastery: Achieving Safe and Efficient Real-World Autonomous Driving with Human-In-The-Loop Reinforcement Learning
Autonomous driving with reinforcement learning (RL) has significant potential. However, applying RL in real-world settings remains challenging due to the need for safe, efficient, and robust learning. Incorporating human expertise into the learning process can help overcome these challenges by reducing risky exploration and improving sample efficiency. In this work, we propose a reward-free, active human-in-the-loop learning method called Human-Guided Distributional Soft Actor-Critic (H-DSAC). …

Domain-Shift-Aware Conformal Prediction for Large Language Models
Zhexiao Lin, Yuanyuan Li, Neeraj Sarna, Yuanyuan Gao, Michael von Gablenz
https://arxiv.org/abs/2510.05566 http…

Domain-Shift-Aware Conformal Prediction for Large Language Models
Large language models have achieved impressive performance across diverse tasks. However, their tendency to produce overconfident and factually incorrect outputs, known as hallucinations, poses risks in real world applications. Conformal prediction provides finite-sample, distribution-free coverage guarantees, but standard conformal prediction breaks down under domain shift, often leading to under-coverage and unreliable prediction sets. We propose a new framework called Domain-Shift-Aware Conf…

Is it Gaussian? Testing bosonic quantum states
Filippo Girardi, Freek Witteveen, Francesco Anna Mele, Lennart Bittel, Salvatore F. E. Oliviero, David Gross, Michael Walter
https://arxiv.org/abs/2510.07305

Is it Gaussian? Testing bosonic quantum states
Gaussian states are widely regarded as one of the most relevant classes of continuous-variable (CV) quantum states, as they naturally arise in physical systems and play a key role in quantum technologies. This motivates a fundamental question: given copies of an unknown CV state, how can we efficiently test whether it is Gaussian? We address this problem from the perspective of representation theory and quantum learning theory, characterizing the sample complexity of Gaussianity testing as a fu…

Active Semantic Perception
Huayi Tang, Pratik Chaudhari
https://arxiv.org/abs/2510.05430 https://arxiv.org/pdf/2510.05430

Active Semantic Perception
We develop an approach for active semantic perception which refers to using the semantics of the scene for tasks such as exploration. We build a compact, hierarchical multi-layer scene graph that can represent large, complex indoor environments at various levels of abstraction, e.g., nodes corresponding to rooms, objects, walls, windows etc. as well as fine-grained details of their geometry. We develop a procedure based on large language models (LLMs) to sample plausible scene graphs of unobser…

how to get a bunch of hosts on the internet to generate some sample TCP SYNs for you:
http://rage4.infra.grebedoc.dev/
mastodons gooo

Data-driven Practical Stabilization of Nonlinear Systems via Chain Policies: Sample Complexity and Incremental Learning
Roy Siegelmann, Enrique Mallada
https://arxiv.org/abs/2510.03982

Data-driven Practical Stabilization of Nonlinear Systems via Chain Policies: Sample Complexity and Incremental Learning
We propose a method for data-driven practical stabilization of nonlinear systems with provable guarantees, based on the concept of Nonparametric Chain Policies (NCPs). The approach employs a normalized nearest-neighbor rule to assign, at each state, a finite-duration control signal derived from stored data, after which the process repeats. Unlike recent works that model the system as linear, polynomial, or polynomial fraction, we only assume the system to be locally Lipschitz. Our analysis buil…

Can language models boost the power of randomized experiments without statistical bias?
Xinrui Ruan, Xinwei Ma, Yingfei Wang, Waverly Wei, Jingshen Wang
https://arxiv.org/abs/2510.05545

Can language models boost the power of randomized experiments without statistical bias?
Randomized experiments or randomized controlled trials (RCTs) are gold standards for causal inference, yet cost and sample-size constraints limit power. Meanwhile, modern RCTs routinely collect rich, unstructured data that are highly prognostic of outcomes but rarely used in causal analyses. We introduce CALM (Causal Analysis leveraging Language Models), a statistical framework that integrates large language models (LLMs) predictions with established causal estimators to increase precision whil…

Dormant BH candidates from Gaia DR3 summary diagnostics
Johanna M\"uller-Horn, Hans-Walter Rix, Kareem El-Badry, Ben Pennell, Matthew Green, Jiadong Li, Rhys Seeburger
https://arxiv.org/abs/2510.05982

Dormant BH candidates from Gaia DR3 summary diagnostics
We present a rigorous identification of candidates for dormant black holes (BHs) and neutron stars (NSs) in binaries using summary statistics from Gaia DR3, rather than full orbital solutions. Although Gaia astrometric orbits have already revealed a small sample of compact object binaries, many systems remain undetected due to stringent quality cuts imposed on the published orbits. Using a forward-modelling framework that simulates Gaia observables, in particular the renormalised unit weight er…

Angular BAO Measurements with the DESI DR1 BGS Sample
Paula S. Ferreira, Ulisses Ribeiro, Pedro da Silveira Ferreira, Cl\'ecio R. Bom, Armando Bernui
https://arxiv.org/abs/2510.02144

Angular BAO Measurements with the DESI DR1 BGS Sample
We employ a model-independent approach in both the correlation function estimation and the angular BAO feature estimation by computing the angular two-point correlation function. First, we conducted a series of tests to the available DESI tracers to check their representativeness to angular clustering; the result was that, considering the completeness of the first data release across the footprint, we could only make use of the BGS sample for the effective redshifts 0.21 (BGS1) and 0.25 (BGS2).…

Updated Radio Sigma-D Relation and Distances to the Shell-Like Galactic Supernova Remnants -- IV
D. Uro\v{s}evi\'c, B. Vukoti\'c, M. An{\dj}eli\'c, N. Mladenovi\'c
https://arxiv.org/abs/2510.03410

Updated Radio Sigma-D Relation and Distances to the Shell-Like Galactic Supernova Remnants -- IV
We present a new selected sample of 69 Galactic supernova remnants (SNRs) for calibration of radio $Σ-D$ relation at 1 GHz. Calibrators with the most reliable distances were selected through an extensive literature search. The calibration is performed using kernel smoothing of the selected sample of calibrators in $Σ-D$ plane and an orthogonal offsets fitting procedure. We use the obtained calibration to derive the distances to 164 Galactic SNRs and 27 new detected SNRs/SNR candidates with no…

Researching DIY solutions for preparing digital negatives for my salt/kallitype printing experiments. Working on a little curve fitting tool/library (of course using https://thi.ng/umbrella) for computing tone mapping curves derived from sample swatches (here 5% steps of gray/density). The screenshot shows 2nd - 5th d…

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

Updated https://adrianroselli.com/2025/10/openai-aria-and-seo-making-the-web-worse.html to link to a post from Stephanie Stimac that I missed, Simon Willison on prompt injection attacks, a sample attack from Brave, and Chris Coyier’s surprisingly long lis…

OpenAI, ARIA, and SEO: Making the Web Worse
OpenAI has announced it’s launched a new browser, Atlas, with ChatGPT built in. For those familiar with ARIA, OpenAI outlines what to expect (I left the code as I found it, other than removing the target): We’ll continue to make Atlas better, and our roadmap includes multi-profile support, improved developer…

🇺🇦 Auf radioeins läuft...
Foxwarren:
🎵 Listen2me
#NowPlaying #Foxwarren
https://foxwarren.bandcamp.com/track/listen2me-stem20-sample-listen2me
https://open.spotify.com/track/29WWHCuzU0OCWTfiBKbOm1

A Langevin Model-Based Magneto-Optic Response SuperParamagnetic Nanoparticles Recorded with a Michelson Interferometer Setup
Syed Azer Reza, Maarij Syed
https://arxiv.org/abs/2510.07209

A Langevin Model-Based Magneto-Optic Response SuperParamagnetic Nanoparticles Recorded with a Michelson Interferometer Setup
In this paper, we provide expressions for the detected optical irradiance for magneto-optic characterization of superparamagnetic nanoparticles (SPNs) in solution imparting Faraday rotation (FR) to an optical beam passing through the sample solution. For our analysis, we assume a Langevin model for SPN samples and show the presence of odd and even harmonics for SPN samples characterized with a Michelson interferometer. This optical geometry is potentially useful in understanding nonlinear SPN F…

Optimality and computational barriers in variable selection under dependence
Ming Gao, Bryon Aragam
https://arxiv.org/abs/2510.03990 https://arxiv.org/pdf/…

Optimality and computational barriers in variable selection under dependence
We study the optimal sample complexity of variable selection in linear regression under general design covariance, and show that subset selection is optimal while under standard complexity assumptions, efficient algorithms for this problem do not exist. Specifically, we analyze the variable selection problem and provide the optimal sample complexity with exact dependence on the problem parameters for both known and unknown sparsity settings. Moreover, we establish a sample complexity lower boun…

🗳️🇺🇸 Hey, Maine! 2 weeks from tomorrow (Nov 4) you’ve got a referendum that could shape elections for years. It may be an off-year but the outcome will sway every election from now on.
Bipartisan info at https://ballotpedia.org/wiki/index.php?title=Sample_Ballot…

Using #PHP arrays as pseudo-objects is almost never the right answer. They're less self-documenting, slower, worse on memory, and more bug prone.
https://peakd.com/php/@crell/php-use-a

Efficiently Generating Correlated Sample Paths from Multi-step Time Series Foundation Models
Ethan Baron, Boris Oreshkin, Ruijun Ma, Hanyu Zhang, Kari Torkkola, Michael W. Mahoney, Andrew Gordon Wilson, Tatiana Konstantinova
https://arxiv.org/abs/2510.02224

Efficiently Generating Correlated Sample Paths from Multi-step Time Series Foundation Models
Many time series applications require access to multi-step forecast trajectories in the form of sample paths. Recently, time series foundation models have leveraged multi-step lookahead predictions to improve the quality and efficiency of multi-step forecasts. However, these models only predict independent marginal distributions for each time step, rather than a full joint predictive distribution. To generate forecast sample paths with realistic correlation structures, one typically resorts to …

Neon: Negative Extrapolation From Self-Training Improves Image Generation
Sina Alemohammad, Zhangyang Wang, Richard G. Baraniuk
https://arxiv.org/abs/2510.03597 https://

Neon: Negative Extrapolation From Self-Training Improves Image Generation
Scaling generative AI models is bottlenecked by the scarcity of high-quality training data. The ease of synthesizing from a generative model suggests using (unverified) synthetic data to augment a limited corpus of real data for the purpose of fine-tuning in the hope of improving performance. Unfortunately, however, the resulting positive feedback loop leads to model autophagy disorder (MAD, aka model collapse) that results in a rapid degradation in sample quality and/or diversity. In this pape…

Estimation of intrinsic fast radio burst width and scattering distributions from CRAFT data
C. W. James, J. Hoffmann, J. X. Prochaska, M. Glowacki
https://arxiv.org/abs/2510.05654

Estimation of intrinsic fast radio burst width and scattering distributions from CRAFT data
The intrinsic width and scattering distributions of fast radio bursts (FRBs) inform on their emission mechanism and local environment, and act as a source of detection bias and, hence, an obfuscating factor when performing FRB population and cosmological studies. Here, we utilise a sample of 29 FRBs with measured high-time-resolution properties and known redshift, which were detected using the Australian Square Kilometre Array Pathfinder (ASKAP) by the Commensal Real-time ASKAP Fast Transients …

Disk fraction among free-floating planetary-mass objects in Upper Scorpius
Tommy Rodrigues, Herv\'e Bouy, Sean N. Raymond, Eduardo L. Mart\'in, Emmanuel Bertin, Javier Olivares, David Barrado, N\'uria Hu\'elamo, Motohide Tamura, N\'uria Miret Roig, Phillip A. B. Galli, Jean-Charles Cuillandre
https://arxiv.org/abs/2510.…

Disk fraction among free-floating planetary-mass objects in Upper Scorpius
Free-floating planetary-mass objects (FFPs) have been detected through direct imaging within several young, nearby star-forming regions. The properties of circumstellar disks around these objects may provide a valuable probe into their origin, but is currently limited by the small sizes of the sample explored. We aim to perform a statistical study of the occurrence of circumstellar disks down to the planetary-mass regime. We performed a systematic survey of disks among the population identified…

The Star-forming Main Sequence and Bursty Star-formation Histories at $z>1.4$ in JADES and AURORA
Leonardo Clarke, Alice E. Shapley, Natalie Lam, Michael W. Topping, Gabriel B. Brammer, Ryan L. Sanders, Naveen A. Reddy, Shreya Karthikeyan
https://arxiv.org/abs/2510.06681

The Star-forming Main Sequence and Bursty Star-formation Histories at $z>1.4$ in JADES and AURORA
We analyze JWST spectroscopic and HST+JWST photometric observations of 659 star-forming galaxies at $1.4 < z < 9$ from DR3 of the JADES survey and the AURORA Cycle 1 program. We measure the star-forming main sequence (SFMS) for galaxies above $10^{8.5}\rm\ M_\odot$ where the sample is largely representative, estimating star-formation rates (SFRs) using the H$α$ line flux and rest-frame far UV (1600Å) continuum measurements, each independently corrected for dust attenuation. We find that the i…

On Improvement of Control Chart using Repetitive Sampling for Monitoring Process Mean
Fahad Rafique, Saadia Masood, Shabbir Ahmad, Sadaf Amin
https://arxiv.org/abs/2510.05086 ht…

On Improvement of Control Chart using Repetitive Sampling for Monitoring Process Mean
In the practical industry, the most commonly used application of statistical analysis for monitoring the process mean is the control chart. Control charts are generated based on the presumption that we have a sample from a stable process. The control chart then provides a graphical display to test this presumption. In the existing estimator \textcolor{red}{$Mr$}, researchers use a technique involving repetitive sampling along with an auxiliary variable for detecting and monitoring the statistic…

MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
Jan Ole von Hartz, Lukas Schweizer, Joschka Boedecker, Abhinav Valada
https://arxiv.org/abs/2509.24956

MSG: Multi-Stream Generative Policies for Sample-Efficient Robotic Manipulation
Generative robot policies such as Flow Matching offer flexible, multi-modal policy learning but are sample-inefficient. Although object-centric policies improve sample efficiency, it does not resolve this limitation. In this work, we propose Multi-Stream Generative Policy (MSG), an inference-time composition framework that trains multiple object-centric policies and combines them at inference to improve generalization and sample efficiency. MSG is model-agnostic and inference-only, hence widely…

Gearing up for tonight's decap run.
In the queue: 5x PIC12F683 for delayering, XC6SLX25, XC7S25, ATSAMA5D27, 25AA1024
I'm not bothering to label the sample beakers because I know what most of these chips will look like from having seen other parts in the family. The ATSAM is the main unknown.
Anybody know what foundry it was made at? What node? We'll find out soon I guess.

Relative Information Gain and Gaussian Process Regression
Hamish Flynn
https://arxiv.org/abs/2510.04277 https://arxiv.org/pdf/2510.04277

Relative Information Gain and Gaussian Process Regression
The sample complexity of estimating or maximising an unknown function in a reproducing kernel Hilbert space is known to be linked to both the effective dimension and the information gain associated with the kernel. While the information gain has an attractive information-theoretic interpretation, the effective dimension typically results in better rates. We introduce a new quantity called the relative information gain, which measures the sensitivity of the information gain with respect to the o…

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

Topic Modeling as Long-Form Generation: Can Long-Context LLMs revolutionize NTM via Zero-Shot Prompting?
Xuan Xu, Haolun Li, Zhongliang Yang, Beilin Chu, Jia Song, Moxuan Xu, Linna Zhou
https://arxiv.org/abs/2510.03174

Topic Modeling as Long-Form Generation: Can Long-Context LLMs revolutionize NTM via Zero-Shot Prompting?
Traditional topic models such as neural topic models rely on inference and generation networks to learn latent topic distributions. This paper explores a new paradigm for topic modeling in the era of large language models, framing TM as a long-form generation task whose definition is updated in this paradigm. We propose a simple but practical approach to implement LLM-based topic model tasks out of the box (sample a data subset, generate topics and representative text with our prompt, text assi…

Quantum Subgradient Estimation for Conditional Value-at-Risk Optimization
Vasilis Skarlatos, Nikos Konofaos
https://arxiv.org/abs/2510.04736 https://arxiv.…

Quantum Subgradient Estimation for Conditional Value-at-Risk Optimization
Conditional Value-at-Risk (CVaR) is a leading tail-risk measure in finance, central to both regulatory and portfolio optimization frameworks. Classical estimation of CVaR and its gradients relies on Monte Carlo simulation, incurring $O(1/ε^2)$ sample complexity to achieve $ε$-accuracy. In this work, we design and analyze a quantum subgradient oracle for CVaR minimization based on amplitude estimation. Via a tripartite proposition, we show that CVaR subgradients can be estimated with $O(1/ε)$…

Understanding an origin of palladium in metal-poor stars based on the non-LTE analysis of Pd~I lines
L. Mashonkina, A. Smogorzhevskii
https://arxiv.org/abs/2510.06968 https://…

Understanding an origin of palladium in metal-poor stars based on the non-LTE analysis of Pd~I lines
Palladium is one of poorly observed neutron-capture elements. Abundance determinations for stellar samples covering a broad metallicity range are needed for better understanding the mechanisms of Pd synthesis during the Galaxy evolution. We aim to obtain accurate abundances of Pd for the Sun and the sample of metal-poor stars based on the non-local thermodynamic equilibrium (non-LTE) line formation for Pd~I. We present a new, comprehensive model atom of Pd~I. Abundances of Pd, Sr, Ba, and Eu we…

The Prevalence of Bursty Star Formation in Low-Mass Galaxies at z=1-7 from H{\alpha}-to-UV Diagnostics
Marissa N. Perry (The University of Texas at Austin, Department of Astronomy), Anthony J. Taylor (The University of Texas at Austin, Department of Astronomy), Oscar A. Chavez Ortiz (The University of Texas at Austin, Department of Astronomy), Steven L. Finkelstein (The University of Texas at Austin, Department of Astronomy), Gene C. K. Leung (MIT Kavli Institute for Astrophysics and S…

The Prevalence of Bursty Star Formation in Low-Mass Galaxies at z=1-7 from Hα-to-UV Diagnostics
We present an analysis of bursty star-formation histories (SFHs) of 346 star-forming galaxies at $1\lesssim z<7$, selected from JWST/NIRSpec G395M and PRISM spectroscopy provided by the CEERS and RUBIES surveys. We analyze the correlation of star-formation rate vs. stellar mass (the star-forming main sequence, SFMS) for our sample and find no significant difference between the intrinsic scatter in the H$α$-based SFMS and the UV-continuum-based SFMS. However, the diagnostic power of the SFMS is…

Series C, Episode 07 - Children of Auron
DERAL: Is that all it takes, then? A sample of blood?
FRANTON: It's the genetic print we need. All body cells with a nucleus carry that. The white cells are here. As long as they're capable of differentiation, they're capable of growth, into another you.
https://blake.torpid…

Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective
Weixin Wang, Haoyang Zheng, Guang Lin, Wei Deng, Pan Xu
https://arxiv.org/abs/2510.05023 https:…

Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective
Most existing approximate Thompson Sampling (TS) algorithms for multi-armed bandits use Stochastic Gradient Langevin Dynamics (SGLD) or its variants in each round to sample from the posterior, relaxing the need for conjugacy assumptions between priors and reward distributions in vanilla TS. However, they often require approximating a different posterior distribution in different round of the bandit problem. This requires tricky, round-specific tuning of hyperparameters such as dynamic learning …

Prebiotic organic compounds in samples of asteroid #Bennu indicate heterogeneous aqueous alteration: https://www.pnas.org/doi/10.1073/pnas.2512461122 -> Scientists find evidence that an asteroid contains tryptophan: https://edition.cnn.com/2025/11/27/science/tryptophan-asteroid-bennu-nasa-sample

Modular and Adaptive Conformal Prediction for Sequential Models via Residual Decomposition
William Zhang, Saurabh Amin, Georgia Perakis
https://arxiv.org/abs/2510.04406 https://…

Modular and Adaptive Conformal Prediction for Sequential Models via Residual Decomposition
Conformal prediction offers finite-sample coverage guarantees under minimal assumptions. However, existing methods treat the entire modeling process as a black box, overlooking opportunities to exploit modular structure. We introduce a conformal prediction framework for two-stage sequential models, where an upstream predictor generates intermediate representations for a downstream model. By decomposing the overall prediction residual into stage-specific components, our method enables practition…

Beyond Regularization: Inherently Sparse Principal Component Analysis
Jan O. Bauer
https://arxiv.org/abs/2510.03729 https://arxiv.org/pdf/2510.03729…

Beyond Regularization: Inherently Sparse Principal Component Analysis
Sparse principal component analysis (sparse PCA) is a widely used technique for dimensionality reduction in multivariate analysis, addressing two key limitations of standard PCA. First, sparse PCA can be implemented in high-dimensional low sample size settings, such as genetic microarrays. Second, it improves interpretability as components are regularized to zero. However, over-regularization of sparse singular vectors can cause them to deviate greatly from the population singular vectors, pote…

A chemodynamical study of $r$-process-enhanced stars
Pallavi Saraf (PRL), Thirupathi Sivarani, Carlos Allende Prieto, Shashikiran Ganesh, Drisya Karinkuzhi
https://arxiv.org/abs/2510.06630

A chemodynamical study of $r$-process-enhanced stars
The $r$-process enrichment in the Galaxy still remains elusive with regard to its nucleosynthesis conditions and the astrophysical sites where it occurs. As part of ongoing efforts to pinpoint the origin of chemically peculiar $r$-process-enhanced (RPE) stars, we concentrate in this study on the kinematics of RPE stars to investigate possible variations in the $r$-process enrichment among the Galactic components. We calculate the orbital parameters of a sample of 472 metal-poor RPE stars and as…

Beyond the stars: Linking H$\alpha$ sizes, kinematics, and star formation in galaxies at $z\approx 4-6$ with JWST grism surveys and $\texttt{geko}$
A. Lola Danhaive, Sandro Tacchella, William McClymont, Brant Robertson, Stefano Carniani, Courtney Carreira, Eiichi Egami, Andrew J. Bunker, Emma Curtis-Lake, Daniel J. Eisenstein, Zhiyuan Ji, Benjamin D. Johnson, Marcia Rieke, Natalia C. Villanueva, Christopher N. A. Willmer, Chris Willot, Zihao Wu, Yongda Zhu

Beyond the stars: Linking H$α$ sizes, kinematics, and star formation in galaxies at $z\approx 4-6$ with JWST grism surveys and $\texttt{geko}$
Understanding how galaxies assemble their mass during the first billion years of cosmic time is a central goal of extragalactic astrophysics, yet joint constraints on their sizes and kinematics remain scarce. We present one of the first statistical studies of the $\mathrm{H}α$ size-mass relation at high redshift with a sample of 213 galaxies at spectroscopic redshifts of $z\approx 4-6$ from the FRESCO and CONGRESS NIRCam grism surveys. We measure the $\mathrm{H}α$ morphology and kinematics of…

On Cryptography and Distribution Verification, with Applications to Quantum Advantage
Bruno Cavalar, Eli Goldin, Matthew Gray, Taiga Hiroka, Tomoyuki Morimae
https://arxiv.org/abs/2510.05028

On Cryptography and Distribution Verification, with Applications to Quantum Advantage
One of the most fundamental problems in the field of hypothesis testing is the identity testing problem: whether samples from some unknown distribution $\mathcal{G}$ are actually from some explicit distribution $\mathcal{D}$. It is known that when the distribution $\mathcal{D}$ has support $[N]$, the optimal sample complexity for the identity testing problem is roughly $O(\sqrt{N})$. However, many distributions of interest, including those which can be sampled efficiently, have exponential supp…

Sample-Efficient Differentially Private Fine-Tuning via Gradient Matrix Denoising
Ali Dadsetan, Frank Rudzicz
https://arxiv.org/abs/2510.01137 https://arxi…

Sample-Efficient Differentially Private Fine-Tuning via Gradient Matrix Denoising
We address the challenge of sample efficiency in differentially private fine-tuning of large language models (LLMs) using DP-SGD. While DP-SGD provides strong privacy guarantees, the added noise significantly increases the entropy of gradient matrices, disrupting their low-rank structure and slowing optimization. We propose a post-processing algorithm that leverages random matrix theory to denoise gradients, restore low-rank structure, and improve alignment with the original signal. Applied to …

General Divergence Regularized Optimal Transport: Sample Complexity and Central Limit Theorems
Jiaping Yang, Yunxin Zhang
https://arxiv.org/abs/2510.02489 https://

General Divergence Regularized Optimal Transport: Sample Complexity and Central Limit Theorems
Optimal transport has emerged as a fundamental methodology with applications spanning multiple research areas in recent years. However, the convergence rate of the empirical estimator to its population counterpart suffers from the curse of dimensionality, which prevents its application in high-dimensional spaces. While entropic regularization has been proven to effectively mitigate the curse of dimensionality and achieve a parametric convergence rate under mild conditions, these statistical gua…

twitter: Twitter followers (2010)
A directed network of following relationships from Twitter, from a snowball sample crawl across "quality" users in 2009. A directed edge (i, j) indicates that user i follows user j.
This network has 465017 nodes and 834797 edges.
Tags: Social, Online, Unweighted
https://network…

H I Properties of Field Galaxies at $\boldsymbol{z\approx 0.2}$-0.6: Insights into Declining Cosmic Star Formation
David DePalma, Neeraj Gupta, Hsiao-Wen Chen, Robert A. Simcoe, Sergei Balashev, Erin Boettcher, Sebastiano Cantalupo, Mandy C. Chen, Fran\c{c}oise Combes, Claude-Andr\'e Faucher-Gigu\`ere, Sean D. Johnson, Hans-Rainer Kl\"ockner, Jens-Kristian Krogager, Jennifer I-Hsiu Li, Sebasti\'an L\'opez, Pasquier Noterdaeme, Patrick Petitjean, Zhijie Qu, Gwen C. Rudi…

H I Properties of Field Galaxies at $\boldsymbol{z\approx 0.2}$-0.6: Insights into Declining Cosmic Star Formation
We report statistically significant detection of H I 21-cm emission from intermediate-redshift ($z\approx0.2$-0.6) galaxies. By leveraging multi-sightline galaxy survey data from the Cosmic Ultraviolet Baryon Survey (CUBS) and deep radio observations from the MeerKAT Absorption Line Survey (MALS), we have established a sample of $\approx6000$ spectroscopically identified galaxies in 11 distinct fields to constrain the neutral gas content at intermediate redshifts. The galaxies sample a broad ra…

Exploring Stellar Activity in a Sample of Active M Dwarfs
A. S. Rajpurohit, V. Kumar, K. Srivastava Mudit, L. Labadie, K. Rajpurohit, J. G. Fernandez-Trincado
https://arxiv.org/abs/2510.02693

Exploring Stellar Activity in a Sample of Active M Dwarfs
Most M dwarfs show higher chromospheric activity, often exceeding solar levels. Characterizing stellar activity is essential, particularly since these stars are prime targets in the search for habitable exoplanets. We investigate the stellar activity of active M dwarfs using TESS photometry combined with spectroscopic observations. We explore relations between flare occurrence rate (FOR), flare energies, rotation period, starspot filling factor, and chromospheric indicators. We also examine cor…

PIC12F683 sample 2H6, after 14 HF etch cycles and a clean.
This sample has now been imaged 30 times, ranging from fresh after decap to the current state, after each etch, after cleaning passes to remove loose debris, and sometimes at both 20x and 100x in the same state.
This sample is now mostly at via1, but there's still upper layer visible in the seal ring and in the analog IPs.
It's now imaging at 100x. Things go slow because a full focus-stacked 100x image is 10…

Double Descent as a Lens for Sample Efficiency in Autoregressive vs. Discrete Diffusion Models
Ahmad Fraij, Sam Dauncey
https://arxiv.org/abs/2509.24974 https://

Double Descent as a Lens for Sample Efficiency in Autoregressive vs. Discrete Diffusion Models
Data scarcity drives the need for more sample-efficient large language models. In this work, we use the double descent phenomenon to holistically compare the sample efficiency of discrete diffusion and autoregressive models. We show that discrete diffusion models require larger capacity and more training epochs to escape their underparameterized regime and reach the interpolation threshold. In the strongly overparameterized regime, both models exhibit similar behavior, with neither exhibiting a…

Self-Speculative Masked Diffusions
Andrew Campbell, Valentin De Bortoli, Jiaxin Shi, Arnaud Doucet
https://arxiv.org/abs/2510.03929 https://arxiv.org/pdf/2…

Self-Speculative Masked Diffusions
We present self-speculative masked diffusions, a new class of masked diffusion generative models for discrete data that require significantly fewer function evaluations to generate samples. Standard masked diffusion models predict factorized logits over currently masked positions. A number of masked positions are then sampled, however, the factorization approximation means that sampling too many positions in one go leads to poor sample quality. As a result, many simulation steps and therefore n…

Empirical partially Bayes two sample testing
Wanyi Ling, Wufang Hong, Nikolaos Ignatiadis
https://arxiv.org/abs/2510.00432 https://arxiv.org/pdf/2510.00432…

Empirical partially Bayes two sample testing
A common task in high-throughput biology is to test for differences in means between two samples across thousands of features (e.g., genes or proteins), often with only a handful of replicates per sample. Moderated t-tests handle this problem by assuming normality and equal variances, and by applying the empirical partially Bayes principle: a prior is posited and estimated for the nuisance parameters (variances) but not for the primary parameters (means). This approach has been highly successfu…

Learning to Sample: Reinforcement Learning-Guided Sampling for Autonomous Vehicle Motion Planning
Korbinian Moller, Roland Stroop, Mattia Piccinini, Alexander Langmann, Johannes Betz
https://arxiv.org/abs/2509.24313

Learning to Sample: Reinforcement Learning-Guided Sampling for Autonomous Vehicle Motion Planning
Sampling-based motion planning is a well-established approach in autonomous driving, valued for its modularity and analytical tractability. In complex urban scenarios, however, uniform or heuristic sampling often produces many infeasible or irrelevant trajectories. We address this limitation with a hybrid framework that learns where to sample while keeping trajectory generation and evaluation fully analytical and verifiable. A reinforcement learning (RL) agent guides the sampling process toward…

Beyond diagnostic-diagrams: A critical exploration on the classification of ionization processes
S. F. S\'anchez, C. Mu\~noz-Tu\~n\'on, J. S\'anchez Almeida, O. Gonz\'alez-Mart\'in, E. P\'erez
https://arxiv.org/abs/2510.07256

Beyond diagnostic-diagrams: A critical exploration on the classification of ionization processes
Optical emission-line diagnostic diagrams, such as the classical BPT, are widely used to identify ionisation mechanisms in galaxies but often suffer from degeneracies, especially when multiple sources coexist. We critically evaluate the effectiveness of these diagnostics in distinguishing star-forming galaxies, retired galaxies (RGs), and active galactic nuclei (AGNs), and propose refined methods to reduce misclassifications. Using a large sample of nearby galaxies from the NASA-Sloan Atlas cro…

ResCP: Reservoir Conformal Prediction for Time Series Forecasting
Roberto Neglia, Andrea Cini, Michael M. Bronstein, Filippo Maria Bianchi
https://arxiv.org/abs/2510.05060 https…

ResCP: Reservoir Conformal Prediction for Time Series Forecasting
Conformal prediction offers a powerful framework for building distribution-free prediction intervals for exchangeable data. Existing methods that extend conformal prediction to sequential data rely on fitting a relatively complex model to capture temporal dependencies. However, these methods can fail if the sample size is small and often require expensive retraining when the underlying data distribution changes. To overcome these limitations, we propose Reservoir Conformal Prediction (ResCP), a…

Warm absorber outflows in radio-loud active galactic nucleus 3C~59
Yijun Wang, Tao Wang, Junjie Mao, Yerong Xu, Zhicheng He, Zheng Zhou, Chen Li, Yongquan Xue, Jiayi Chen, Fangzheng Shi, Missagh Mehdipour
https://arxiv.org/abs/2510.06752

Warm absorber outflows in radio-loud active galactic nucleus 3C~59
Both jets and ionized outflows in active galactic nuclei (AGNs) are thought to play important roles in affecting the star formation and evolution of host galaxies, but their relationship is still unclear. As a pilot study, we performed a detailed spectral analysis for a radio-loud (RL) AGN 3C~59 ($z=0.1096$) by systematically considering various factors that may affect the fitting results, and thereby establishing a general spectral fitting strategy for subsequent research with larger sample. 3…

The Accretion Disk Size Problem in AGN Disk Reverberation Mapping is an Obscuration Effect: A Uniform AGN Sample Study with Swift
Collin Lewin, Erin Kara, Christos Panagiotou, Edward M. Cackett, Jonathan Gelbord, Juan V. Hern\'andez Santisteban, Keith Horne, Gerard A. Kriss
https://arxiv.org/abs/2509.25315

The Accretion Disk Size Problem in AGN Disk Reverberation Mapping is an Obscuration Effect: A Uniform AGN Sample Study with Swift
In the past decade, Swift has performed several AGN high-cadence reverberation mapping campaigns, and generally found that the UV/optical interband lags are $\sim$3 times longer than predicted for a standard thin disk, thus coined "the accretion disk size problem". Here we present a systematic sample of Swift-monitored AGN. In this analysis, we confirm the accretion disk size problem, but find that the lag excess occurs only in the subset of obscured AGN, which show a significantly elevated mea…

Rapid Scaling of Compositional Uncertainty from Sample to Population Levels
Yiran Wang, Martin Lysy, Audrey B\'eliveau
https://arxiv.org/abs/2510.00980 https://

Rapid Scaling of Compositional Uncertainty from Sample to Population Levels
Understanding population composition is essential across ecological, evolutionary, conservation, and resource management contexts. Modern methods such as genetic stock identification (GSI) estimate the proportion of individuals from each subpopulation using genetic data. Ideally, these estimates are obtained through mixture analysis, which captures both sampling and genetic uncertainty. However, historical datasets often rely on individual assignment methods that only account for sample-level u…

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity
Ivan Lau, Jonathan Scarlett
https://arxiv.org/abs/2509.21940 https://arxiv.org/pdf/250…

Sequential 1-bit Mean Estimation with Near-Optimal Sample Complexity
In this paper, we study the problem of distributed mean estimation with 1-bit communication constraints. We propose a mean estimator that is based on (randomized and sequentially-chosen) interval queries, whose 1-bit outcome indicates whether the given sample lies in the specified interval. Our estimator is $(ε, δ)$-PAC for all distributions with bounded mean ($-λ\le \mathbb{E}(X) \le λ$) and variance ($\mathrm{Var}(X) \le σ^2$) for some known parameters $λ$ and $σ$. We derive a sample c…

Abundance of strontium in the Galactic globular cluster 47 Tuc
E. Kolomiecas, A. Ku\v{c}inskas, J. Klevas, V. Dobrovolskas
https://arxiv.org/abs/2510.04722 https://

Abundance of strontium in the Galactic globular cluster 47 Tuc
Aims. We have determined Sr abundance in a sample of 31 red giant branch stars located in the Galactic globular cluster 47 Tuc with the aim to identify potential differences in the Sr abundance between first population (1P, Na-poor) and second population (2P, Na-rich) stars. Methods. We derived the Na and Sr abundances from the archival spectra obtained with the UVES spectrograph. To do this, we used 1D ATLAS9 model atmospheres and a 1D local thermodynamic equilibrium spectral synthesis method.…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
Zhijun Liu, Jiang Hu, Zhidong Bai, Zhihui Lv
https://arxiv.org/abs/2510.04185 h…

Asymptotic distributions of four linear hypotheses test statistics under generalized spiked model
In this paper, we establish the Central Limit Theorem (CLT) for linear spectral statistics (LSSs) of large-dimensional generalized spiked sample covariance matrices, where the spiked eigenvalues may be either bounded or diverge to infinity. Building upon this theorem, we derive the asymptotic distributions of linear hypothesis test statistics under the generalized spiked model, including Wilks' likelihood ratio test statistic U, the Lawley-Hotelling trace test statistic W, and the Bartlett-Nand…

Private Realizable-to-Agnostic Transformation with Near-Optimal Sample Complexity
Bo Li, Wei Wang, Peng Ye
https://arxiv.org/abs/2510.01291 https://arxiv.o…

Private Realizable-to-Agnostic Transformation with Near-Optimal Sample Complexity
The realizable-to-agnostic transformation (Beimel et al., 2015; Alon et al., 2020) provides a general mechanism to convert a private learner in the realizable setting (where the examples are labeled by some function in the concept class) to a private learner in the agnostic setting (where no assumptions are imposed on the data). Specifically, for any concept class $\mathcal{C}$ and error parameter $α$, a private realizable learner for $\mathcal{C}$ can be transformed into a private agnostic le…

Bias-Reduced Estimation of Structural Equation Models
Haziq Jamil, Yves Rosseel, Oliver Kemp, Ioannis Kosmidis
https://arxiv.org/abs/2509.25419 https://arx…

Bias-Reduced Estimation of Structural Equation Models
Finite-sample bias is a pervasive challenge in the estimation of structural equation models (SEMs), especially when sample sizes are small or measurement reliability is low. A range of methods have been proposed to improve finite-sample bias in the SEM literature, ranging from analytic bias corrections to resampling-based techniques, with each carrying trade-offs in scope, computational burden, and statistical performance. We apply the reduced-bias M-estimation framework (RBM, Kosmidis & Lunard…

ZeroShotOpt: Towards Zero-Shot Pretrained Models for Efficient Black-Box Optimization
Jamison Meindl, Yunsheng Tian, Tony Cui, Veronika Thost, Zhang-Wei Hong, Johannes D\"urholt, Jie Chen, Wojciech Matusik, Mina Konakovi\'c Lukovi\'c
https://arxiv.org/abs/2510.03051

ZeroShotOpt: Towards Zero-Shot Pretrained Models for Efficient Black-Box Optimization
Global optimization of expensive, derivative-free black-box functions requires extreme sample efficiency. While Bayesian optimization (BO) is the current state-of-the-art, its performance hinges on surrogate and acquisition function hyper-parameters that are often hand-tuned and fail to generalize across problem landscapes. We present ZeroShotOpt, a general-purpose, pretrained model for continuous black-box optimization tasks ranging from 2D to 20D. Our approach leverages offline reinforcement …

WALLABY Pilot Survey: Characterizing Low Rotation Kinematically Modelled Galaxies
N. Deg, K. Spekkens, N. Arora, R. Dudley, H. White, A. Helias, J. English, T. O'Beirne, V. Kilborn, G. Ferrand, M. L. A. Richardson, B. Catinella, L. Cortese, H. D\'enes, A. Elagali, B. -Q. For, K. Lee-Waddell, J. Rhee, L. Shao, A. X. Shen, L. Staveley-Smith, T. Westmeier, O. I. Wong

WALLABY Pilot Survey: Characterizing Low Rotation Kinematically Modelled Galaxies
Many of the tensions in cosmological models of the Universe lie in the low mass, low velocity regime. Probing this regime requires a statistically significant sample of galaxies with well measured kinematics and robustly measured uncertainties. WALLABY, as a wide area, untargetted HI survey is well positioned to construct this sample. As a first step towards this goal we develop a framework for testing kinematic modelling codes in the low resolution, low $S/N$, low rotation velocity regime. We …

JADES Data Release 4 Paper I: Sample Selection, Observing Strategy and Redshifts of the complete spectroscopic sample
Emma Curtis-Lake, Alex J. Cameron, Andrew J. Bunker, Jan Scholtz, Stefano Carniani, Eleonora Parlanti, Francesco D'Eugenio, Peter Jakobsen, Christopher N. A. Willmer, Santiago Arribas, William M. Baker, St\'ephane Charlot, Jacopo Chevallard, Chiara Circosta, Mirko Curti, Daniel J. Eisenstein, Kevin Hainline, Zhiyuan Ji, Benjamin D. Johnson, Gareth C. Jones, Robe…

JADES Data Release 4 Paper I: Sample Selection, Observing Strategy and Redshifts of the complete spectroscopic sample
This paper accompanies Data Release 4 of the JWST Deep Extragalactic Survey (JADES), which presents the full NIRSpec spectroscopy of the survey. We provide spectra of 5190 targets across GOODS-North and GOODS-South (including the Hubble Ultra Deep Field), observed with the low-dispersion (R $\sim$ 30-300) prism and three medium-resolution (R $\sim$ 1000) gratings spanning 0.8 $< λ<$ 5.5 microns; 2654 were also observed with the higher-resolution (R $\sim$ 2700) G395H grating. The tiered survey…

A Large Sample of JWST/NIRSpec Brown Dwarfs: New Distant Discoveries
Zhijun Tu, Shu Wang, Xiaodian Chen, Jifeng Liu
https://arxiv.org/abs/2510.02026 https://

A Large Sample of JWST/NIRSpec Brown Dwarfs: New Distant Discoveries
Brown dwarfs are essential probes of stellar and planetary formation, yet their low luminosities pose challenges for detection at large Galactic distances. The James Webb Space Telescope (JWST), with its unprecedented near-infrared sensitivity, enables the discovery and characterization of distant substellar objects, including those in the Milky Way's thick disk and halo. We conducted a systematic search using over 40,000 publicly available JWST/NIRSpec PRISM/CLEAR spectra and identified 68 bro…

Neural Jump ODEs as Generative Models
Robert A. Crowell, Florian Krach, Josef Teichmann
https://arxiv.org/abs/2510.02757 https://arxiv.org/pdf/2510.02757…

Neural Jump ODEs as Generative Models
In this work, we explore how Neural Jump ODEs (NJODEs) can be used as generative models for Itô processes. Given (discrete observations of) samples of a fixed underlying Itô process, the NJODE framework can be used to approximate the drift and diffusion coefficients of the process. Under standard regularity assumptions on the Itô processes, we prove that, in the limit, we recover the true parameters with our approximation. Hence, using these learned coefficients to sample from the correspond…

Suzaku observations of outskirts of nearby clusters and groups: I. electron density and gas fraction to the virial radius
Kyoko Matsushita, Marie Kondo, Kosuke Sato, Toru Sasaki, Nobuhiro Okabe, Kotaro Fukushima
https://arxiv.org/abs/2510.04523

Suzaku observations of outskirts of nearby clusters and groups: I. electron density and gas fraction to the virial radius
We present an analysis of Suzaku observations of 14 nearby galaxy clusters and groups (z < 0.06), extending radial coverage out to the virial radius (approximately r200). The sample spans a wide mass range, from M500 about 2x10^13 to 7x10^14 solar masses, and includes well-studied systems such as Coma, Perseus, and Virgo. We carefully modeled all background components, including the soft X-ray foregrounds (the Local Hot Bubble, Milky Way Halo, and super-virial temperature components), the cosmi…

A GLIMPSE into the very faint-end of the H$\beta$ [OIII]$\lambda\lambda$4960,5008 luminosity function at z=7-9 behind Abell S1063
Damien Korber, Iryna Chemerynska, Lukas J. Furtak, Hakim Atek, Ryan Endsley, Daniel Schaerer, John Chisholm, Alberto Saldana-Lopez, Angela Adamo, Julian B. Mu\~noz, Pascal A. Oesch, Romain Meyer, Rui Marques-Chaves, Seiji Fujimoto
ht…

A GLIMPSE into the very faint-end of the H$β$+[OIII]$λλ$4960,5008 luminosity function at z=7-9 behind Abell S1063
We use the ultra-deep GLIMPSE JWST/NIRCam survey to constrain the faint-end of the H$β$+[OIII]$λλ$4960,5008 luminosity function (LF) down to $10^{39}$ erg/s at z=7-9 behind the lensed Hubble Frontier Field Abell S1063. We perform SED fitting on a Lyman-Break Galaxy sample, measuring combined H$β$+[OIII] fluxes to construct the emission-line LF. The resulting LF ($α$=-1.55 to -1.78) is flatter than the UV LF ($α<-2$), indicating a lower number density of low H$β$+[OIII] emitters at fixed …