Tootfinder

xkcd: Geologic Core Sample
https://xkcd.com/3171/

A Set of Generalized Components to Achieve Effective Poison-only Clean-label Backdoor Attacks with Collaborative Sample Selection and Triggers
Zhixiao Wu, Yao Lu, Jie Wen, Hao Sun, Qi Zhou, Guangming Lu
https://arxiv.org/abs/2509.19947

A Set of Generalized Components to Achieve Effective Poison-only Clean-label Backdoor Attacks with Collaborative Sample Selection and Triggers
Poison-only Clean-label Backdoor Attacks aim to covertly inject attacker-desired behavior into DNNs by merely poisoning the dataset without changing the labels. To effectively implant a backdoor, multiple \textbf{triggers} are proposed for various attack requirements of Attack Success Rate (ASR) and stealthiness. Additionally, sample selection enhances clean-label backdoor attacks' ASR by meticulously selecting ``hard'' samples instead of random samples to poison. Current methods 1) usually han…

Scale two-sample testing with arbitrarily missing data
Yijin Zeng, Niall M. Adams, Dean A. Bodenham
https://arxiv.org/abs/2509.20332 https://arxiv.org/pdf/…

Scale two-sample testing with arbitrarily missing data
This work proposes a novel rank-based scale two-sample testing method for univariate, distinct data when a subset of the data may be missing. Our approach is based on mathematically tight bounds of the Ansari-Bradley test statistic in the presence of missing data, and rejects the null hypothesis if the test statistic is significant regardless of the missing values. This proposed scale testing method is then combined with the location testing method proposed by Zeng et al. (2024) using the Holm-…

🇺🇦 #NowPlaying on KEXP's #Early
Cat Stevens:
🎵 Morning Has Broken
#CatStevens
https://weddingmusicproject.bandcamp.com/track/morning-has-broken-wedding-music-sample-cat-stevens
https://open.spotify.com/track/7lJcPqSxbSyDE4bLnXeoqr

Cepheid Metallicity in the Leavitt Law (C--MetaLL) survey: VII. Metallicity dependence of Period-Wesenheit relations based on a homogeneous spectroscopic sample
V. Ripepi, E. Trentin, G. Catanzaro, M. Marconi, A. Bhardwaj, G. Clementini, F. Cusano, G. De Somma, R. Molinaro, T. Sicignano, J. Storm
https://arxiv.org/abs/2508.17447

Cepheid Metallicity in the Leavitt Law (C--MetaLL) survey: VII. Metallicity dependence of Period-Wesenheit relations based on a homogeneous spectroscopic sample
The C-MetaLL project has provided homogeneous spectroscopic abundances of 290 Classical Cepheids (DCEPs) for which we have the intensity-averaged magnitudes in multiple optical and near-infrared (NIR) bands, periods, pulsation modes, and Gaia parallaxes. Our goal is to derive updated period--Wesenheit--metallicity (PWZ) relations using the largest and most homogeneous metallicity sample ever used for such analyses, covering a range of $-1.3<$[Fe/H]$<+0.3$ dex. We computed several optical and NI…

Sample completion, structured correlation, and Netflix problems
Leonardo N. Coregliano, Maryanthe Malliaris
https://arxiv.org/abs/2509.20404 https://arxiv.…

Sample completion, structured correlation, and Netflix problems
We develop a new high-dimensional statistical learning model which can take advantage of structured correlation in data even in the presence of randomness. We completely characterize learnability in this model in terms of VCN${}_{k,k}$-dimension (essentially $k$-dependence from Shelah's classification theory). This model suggests a theoretical explanation for the success of certain algorithms in the 2006~Netflix Prize competition.

Local intricacy and average sample complexity for amenable group actions
J. Huang, Z. Xiao
https://arxiv.org/abs/2509.20738 https://arxiv.org/pdf/2509.2073…

Local intricacy and average sample complexity for amenable group actions
Let $(X,G)$, $(Y,G)$ be two $G$-systems, where $G$ is an infinite countable discrete amenable group and $X$, $Y$ are compact metric spaces. Suppose that $\mathcal{U}$ is a cover of $X$. We first introduce the conditional local topological intricacy $\mathrm{Int}_\mathrm{top} (G,\mathcal{U}|Y)$ and average sample complexity $\mathrm{Asc}_\mathrm{top} (G,\mathcal{U}|Y)$. Given an invariant measure $μ$ of $X$, we study the conditional local measure-theoretical intricacy $\mathrm{Int}_μ…

A sample of 3403 galaxy clusters identified in XMM-Newton X-ray images
Z. S. Yuan, Z. L. Wen, W. Xu, J. L. Han
https://arxiv.org/abs/2509.21031 https://arx…

A sample of 3403 galaxy clusters identified in XMM-Newton X-ray images
Currently, the number of galaxy clusters identified using galaxy data has far exceeded the number derived from intracluster medium data. In this study, we used positional information from large optical cluster catalogues to search for previously unrecognized X-ray galaxy clusters in archival XMM-Newton data. We successfully identified 1490 galaxy clusters in X-ray images for the first time. By incorporating 1913 previously known X-ray clusters, we constructed a sample of 3403 galaxy clusters ob…

Leveraging Temporally Extended Behavior Sharing for Multi-task Reinforcement Learning
Gawon Lee (Seoul National University), Daesol Cho (Seoul National University), H. Jin Kim (Seoul National University)
https://arxiv.org/abs/2509.20766

Leveraging Temporally Extended Behavior Sharing for Multi-task Reinforcement Learning
Multi-task reinforcement learning (MTRL) offers a promising approach to improve sample efficiency and generalization by training agents across multiple tasks, enabling knowledge sharing between them. However, applying MTRL to robotics remains challenging due to the high cost of collecting diverse task data. To address this, we propose MT-Lévy, a novel exploration strategy that enhances sample efficiency in MTRL environments by combining behavior sharing across tasks with temporally extended ex…

Took a few minutes between meetings to upgrade my #htmx #aspnetcore sample demo of “12 days of HTMX-mas". If you're a #dotnet developer or someone interested in web development, it's a breez…

GitHub - khalidabuhakmeh/twelve-days-of-htmx-mas: 12 Days (demos) using Htmx with ASP.NET Core
12 Days (demos) using Htmx with ASP.NET Core. Contribute to khalidabuhakmeh/twelve-days-of-htmx-mas development by creating an account on GitHub.

Frequency Response Identification of Low-Order Systems: Finite-Sample Analysis
Arya Honarpisheh, Mario Sznaier
https://arxiv.org/abs/2508.17142 https://arx…

Frequency Response Identification of Low-Order Systems: Finite-Sample Analysis
This paper proposes a frequency-domain system identification method for learning low-order systems. The identification problem is formulated as the minimization of the l2 norm between the identified and measured frequency responses, with the nuclear norm of the Loewner matrix serving as a regularization term. This formulation results in an optimization problem that can be efficiently solved using standard convex optimization techniques. We derive an upper bound on the sampled-frequency complexi…

RephraseTTS: Dynamic Length Text based Speech Insertion with Speaker Style Transfer
Neeraj Matiyali, Siddharth Srivastava, Gaurav Sharma
https://arxiv.org/abs/2508.17031 https:/…

RephraseTTS: Dynamic Length Text based Speech Insertion with Speaker Style Transfer
We propose a method for the task of text-conditioned speech insertion, i.e. inserting a speech sample in an input speech sample, conditioned on the corresponding complete text transcript. An example use case of the task would be to update the speech audio when corrections are done on the corresponding text transcript. The proposed method follows a transformer-based non-autoregressive approach that allows speech insertions of variable lengths, which are dynamically determined during inference, b…

Clapping: Removing Per-sample Storage for Pipeline Parallel Distributed Optimization with Communication Compression
Boao Kong, Xu Huang, Yuqi Xu, Yixuan Liang, Bin Wang, Kun Yuan
https://arxiv.org/abs/2509.19029

😅 Don't sweat it: New device detects sweat biomarker at minimal perspiration rate
https://medicalxpress.com/news/2025-09-dont-device-biomarker-minimal-perspiration.html

Don't sweat it: New device detects sweat biomarker at minimal perspiration rate
Available on demand, in abundance and containing multiple biomarkers, sweat is an increasingly appealing medium for monitoring health, according to researchers at Penn State. But not everyone—especially critically ill patients—can build up enough sweat to provide a robust enough sample for current analysis techniques.

Two-Sample Testing with Block-Wise Missingness in Multi-Source Data
Kejian Zhang, Muxuan Liang, Robert Maile, Doudou Zhou
https://arxiv.org/abs/2508.17411 https://

Two-Sample Testing with Block-Wise Missingness in Multi-Source Data
Multi-source and multi-modal datasets are increasingly common in scientific research, yet they often exhibit block-wise missingness, where entire data sources or modalities are systematically absent for subsets of subjects. This structured form of missingness presents significant challenges for statistical analysis, particularly for two-sample hypothesis testing. Standard approaches such as imputation or complete-case analysis can introduce bias or result in substantial information loss, especi…

Extending Sample Persistence Variable Reduction for Constrained Combinatorial Optimization Problems
Shunta Ide, Shuta Kikuchi, Shu Tanaka
https://arxiv.org/abs/2509.19280 https:…

The maximum variance of a finite sequence, given its mean, minimum, and maximum
Jules L. Ellis
https://arxiv.org/abs/2508.17525 https://arxiv.org/pdf/2508.…

The maximum variance of a finite sequence, given its mean, minimum, and maximum
This paper derives the maximum variance of a finite sample of real numbers, given their mean, minimum and maximum. As the sample size increases, the maximum variance under these constraints converges from below to the upper bound (maximum - mean)(mean - minimum).

On the sample complexity of semi-supervised multi-objective learning
Tobias Wegel, Geelon So, Junhyung Park, Fanny Yang
https://arxiv.org/abs/2508.17152 https://

On the sample complexity of semi-supervised multi-objective learning
In multi-objective learning (MOL), several possibly competing prediction tasks must be solved jointly by a single model. Achieving good trade-offs may require a model class $\mathcal{G}$ with larger capacity than what is necessary for solving the individual tasks. This, in turn, increases the statistical cost, as reflected in known MOL bounds that depend on the complexity of $\mathcal{G}$. We show that this cost is unavoidable for some losses, even in an idealized semi-supervised setting, where…

🗳️🇺🇸 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…

Closed-form $\ell_r$ norm scaling with data for overparameterized linear regression and diagonal linear networks under $\ell_p$ bias
Shuofeng Zhang, Ard Louis
https://arxiv.org/abs/2509.21181

Closed-form $\ell_r$ norm scaling with data for overparameterized linear regression and diagonal linear networks under $\ell_p$ bias
For overparameterized linear regression with isotropic Gaussian design and minimum-$\ell_p$ interpolator $p\in(1,2]$, we give a unified, high-probability characterization for the scaling of the family of parameter norms $ \\{ \lVert \widehat{w_p} \rVert_r \\}_{r \in [1,p]} $ with sample size. We solve this basic, but unresolved question through a simple dual-ray analysis, which reveals a competition between a signal *spike* and a *bulk* of null coordinates in $X^\top Y$, yielding closed-form …

OmniPlantSeg: Species Agnostic 3D Point Cloud Organ Segmentation for High-Resolution Plant Phenotyping Across Modalities
Andreas Gilson, Lukas Meyer, Oliver Scholz, Ute Schmid
https://arxiv.org/abs/2509.21038

OmniPlantSeg: Species Agnostic 3D Point Cloud Organ Segmentation for High-Resolution Plant Phenotyping Across Modalities
Accurate point cloud segmentation for plant organs is crucial for 3D plant phenotyping. Existing solutions are designed problem-specific with a focus on certain plant species or specified sensor-modalities for data acquisition. Furthermore, it is common to use extensive pre-processing and down-sample the plant point clouds to meet hardware or neural network input size requirements. We propose a simple, yet effective algorithm KDSS for sub-sampling of biological point clouds that is agnostic to …

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…

Formation Of Sub-Structure In Luminous Submillimeter galaxies (FOSSILS): Initial sample and the discovery of a dusty spiral at Cosmic Noon
Ryota Ikeda, Daisuke Iono, Ken-ichi Tadaki, Andrea Silva, the FOSSILS Team
https://arxiv.org/abs/2509.20720

Formation Of Sub-Structure In Luminous Submillimeter galaxies (FOSSILS): Initial sample and the discovery of a dusty spiral at Cosmic Noon
High-resolution far-infrared (FIR) observation of submillimeter galaxies (SMGs) is an effective approach to study the formation of sub-structures in the early epoch of massive galaxies. We present the 870$μ$m continuum images resolved down to sub-kpc scales for 12 SMGs taken by Atacama Large Millimeter/Submillimeter Array (ALMA) as an initial sample of the FOSSILS Survey. We discovered a wide variety of morphological properties, including a two-arm spiral galaxy at $z=2.5$ possibly induced by …

What causes the variation in superconducting properties of UTe$_{2}$?
C. S. Kengle, Noah Schnitzer, M. M. Bordelon, S. M. Thomas, P. F. S. Rosa
https://arxiv.org/abs/2509.20298 …

What causes the variation in superconducting properties of UTe$_{2}$?
Reaching a consensus on the superconducting order parameter of unconventional superconductors remains a central challenge in the field of magnetically-mediated superconductivity. Though UTe$_{2}$ is largely accepted as a rare example of an odd-parity superconductor, its precise order parameter remains highly debated, even at ambient conditions. A key underlying issue is the large sample-to-sample variation in superconducting properties at zero applied pressure and magnetic field. Here, we inves…

Photon-starved polarimetry via functional classical shadows
Matteo Rosati, Miranda Parisi, Linda Sansoni, Eleonora Stefanutti, Andrea Chiuri, Marco Barbieri
https://arxiv.org/abs/2509.19547

Photon-starved polarimetry via functional classical shadows
Polarimetry and optical imaging techniques face challenges in photon-starved scenarios, where the low number of detected photons imposes a trade-off between image resolution, integration time, and sample sensitivity. Here we introduce a quantum-inspired method, functional classical shadows, for reconstructing a polarization profile in the low photon-flux regime. Our method harnesses correlations between neighbouring datapoints, based on the recent realisation that machine learning can estimate …

Crosslisted article(s) found for math.LO. https://arxiv.org/list/math.LO/new
[1/1]:
- Sample completion, structured correlation, and Netflix problems
Leonardo N. Coregliano, Maryanthe Malliaris

Measuring Large Language Models Dependency: Validating the Arabic Version of the LLM-D12 Scale
Sameha AlShakhsi, Ala Yankouskaya, Magnus Liebherr, Raian Ali
https://arxiv.org/abs/2508.17063

Measuring Large Language Models Dependency: Validating the Arabic Version of the LLM-D12 Scale
There is an urgent need for reliable, culturally validated instruments to assess psychological responses to AI in general and large language models (LLMs). This need is global issue, but it is especially urgent among Arabic-speaking populations, where AI and LLMs adoption is accelerating, yet psychometric tools remain limited. This study presents the first validation of the LLM-D12, a dual-dimensional scale assessing Instrumental and Relationship Dependency on LLMs, in an Arab sample. A total o…

Asteroseismic modelling of Kepler Legacy stars including lithium depletion
G. Buldgen, J. B\'etrisey, C. Pezzotti, S. Borisov, A. Noels
https://arxiv.org/abs/2508.18016 http…

Asteroseismic modelling of Kepler Legacy stars including lithium depletion
Context. The Kepler Legacy sample is, to this day, the sample of solar-like oscillators with the most exquisite asteroseismic data. In this work, we carry out a detailed modelling of a subsample of these stars for which the surface lithium abundance has also been observed by the GALAH survey and a photometric surface rotation as been measured. Aims. We aim at studying the impact of additional mixing processes on the asteroseismic modelling of Kepler Legacy G and F-type stars. We also investigat…

Fediverse Programmers:
"I am a programmer with a Fediverse account, and I do most of my code-writing for these type(s) of program(s)."
Please consider boosting for a more representative sample.
#programming #poll

Discovery of Two Highly Scattered Pulsars from Image-Based Circular Polarization Searches with the Australian SKA Pathfinder
Rahul Sengar, David L. Kaplan, Emil Lenc, Akash Anumarlapudi, Natasha Hurley-Walker, Ziteng Wang, Laura Driessen, Dougal Dobie, Tara Murphy
https://arxiv.org/abs/2509.20611

Discovery of Two Highly Scattered Pulsars from Image-Based Circular Polarization Searches with the Australian SKA Pathfinder
We report the discovery and timing of two pulsars from a sample of four circularly polarized sources identified in radio continuum images taken as part of the Australian SKA Pathfinder (ASKAP) Variables and Slow Transients (VAST) survey. Observations with the Parkes (Murriyang) radio telescope confirmed both sources as normal pulsars with high dispersion measures. PSR J1646$-$4451 has a spin period of 217 ms and a dispersion measure (DM) of 928 $\rm cm^{-3} \, pc$, while PSR J1837$-$0616 exhibi…

Optimal estimation for regression discontinuity design with binary outcomes
Takuya Ishihara, Masayuki Sawada, Kohei Yata
https://arxiv.org/abs/2509.18857 https://

DARKSKIES: A suite of super-sampled zoom-in simulations of galaxy clusters with self-interacting dark matter
David Harvey, Yves Revaz, Matthieu Schaller, Aurel Schneider, Ethan Tregidga, Felix Vecchi
https://arxiv.org/abs/2509.19842

DARKSKIES: A suite of super-sampled zoom-in simulations of galaxy clusters with self-interacting dark matter
We present the "DARKSKIES" suite of one hundred, zoom-in hydrodynamic simulations of massive ($M_{200}>5\times10^{14}{\rm M}_\odot)$ galaxy clusters with self-interacting dark matter (SIDM). We super-sample the simulations such that $m_{\rm DM}/m_{\rm gas}\sim0.1$, enabling us to simulate a dark matter particle mass of $m=0.68\times10^{8}M_\odot$ an order of magnitude faster, whilst exploring SIDM in the core of clusters at extremely high resolution. We calibrate the baryonic feedback to produc…

Balancing the exploration-exploitation trade-off in active learning for surrogate model-based reliability analysis via multi-objective optimization
Jonathan A. Moran, Pablo G. Morato
https://arxiv.org/abs/2508.18170

Balancing the exploration-exploitation trade-off in active learning for surrogate model-based reliability analysis via multi-objective optimization
Reliability assessment of engineering systems is often hindered by the need to evaluate limit-state functions through computationally expensive simulations, rendering standard sampling impractical. An effective solution is to approximate the limit-state function with a surrogate model iteratively refined through active learning, thereby reducing the number of expensive simulations. At each iteration, an acquisition strategy selects the next sample by balancing two competing goals: exploration, …

Search for CP violation in e e- -> psi(3770) -> DDbar via D -> KsPi0
Xiao-Yu Li (for BESIII Collaboration)
https://arxiv.org/abs/2508.17819 https://

Search for CP violation in e+e- -> psi(3770) -> DDbar via D -> KsPi0
Utilizing data sample of electron-positron collisions recorded with the BESIII detector at the center-of-mass energies of 3.773~GeV, corresponding to an integrated luminosity of 20.28~fb$^{-1}$, we report the first search for the CP forbidden process $e^+e^- \to ψ(3773) \to D^0\bar{D}^0 \to (K^0_Sπ^0)(K^0_Sπ^0)$. No significant signal is observed. We set the upper limit on the observed cross section to be 7.37~fb, and the upper limit on the joint branching fraction of the C-odd correlated ne…

Atmel ATSAMA5D27. Also not my best work, but hey it's a sample I have so might as well photograph it.
It was desoldered from something but I have no idea what the origin was.
https://siliconprawn.org/map/atmel/atsama5d27/azonenberg_mz_mit20x/…

The Gender Gap in Science Communication on TikTok and YouTube: How Platform Dynamics Shape the Visibility of Female Science Communicators
Maider Eizmendi-Iraola, Sim\'on Pe\~na-Fern\'andez, Jordi Morales-i-Gras
https://arxiv.org/abs/2508.16865

The Gender Gap in Science Communication on TikTok and YouTube: How Platform Dynamics Shape the Visibility of Female Science Communicators
Social media platforms facilitate the dissemination of science and access to it. However, gender inequalities in the participation and visibility of communicators persist. This study examined the differences in reach and audience response between YouTube and TikTok from a gender perspective. To do so, the ten most influential science accounts on YouTube and TikTok were selected, with the sample divided equally between men and women, to conduct a comparative study. A total of 4293 videos on TikT…

Optics for broadband x-ray ptychography
Wiebe Stolp, Silvia Cipiccia, Darren Batey, Matthieu Boone
https://arxiv.org/abs/2508.16953 https://arxiv.org/pdf/2…

Optics for broadband x-ray ptychography
In conventional x-ray ptychography, diffraction data is collected by scanning a sample through a monochromatic, and spatially coherent, x-ray beam. A high-resolution image is then retrieved using an iterative algorithm. Combined with a scan of the incident photon energy, it is also possible to access chemical and elemental information. Although powerful, the high brilliance required currently constrains the method to 3rd and 4th generation synchrotron sources and long scanning times. An alterna…

Monte Carlo on a single sample
Nils Detering, Paul Eisenberg, Nicole Hufnagel
https://arxiv.org/abs/2509.17025 https://arxiv.org/pdf/2509.17025

Monte Carlo on a single sample
In this paper, we consider a Monte Carlo simulation method (MinMC) that approximates prices and risk measures for a range $Γ$ of model parameters at once. The simulation method that we study has recently gained popularity [HS20, FPP22, BDG24], and we provide a theoretical framework and convergence rates for it. In particular, we show that sample-based approximations to $\mathbb{E}_θ[X]$, where $θ$ denotes the model and $\mathbb{E}_θ$ the expectation with respect to the distribution $P_θ$ o…

HemePLM-Diffuse: A Scalable Generative Framework for Protein-Ligand Dynamics in Large Biomolecular System
Rakesh Thakur, Riya Gupta
https://arxiv.org/abs/2508.16587 https://

HemePLM-Diffuse: A Scalable Generative Framework for Protein-Ligand Dynamics in Large Biomolecular System
Comprehending the long-timescale dynamics of protein-ligand complexes is very important for drug discovery and structural biology, but it continues to be computationally challenging for large biomolecular systems. We introduce HemePLM-Diffuse, an innovative generative transformer model that is designed for accurate simulation of protein-ligand trajectories, inpaints the missing ligand fragments, and sample transition paths in systems with more than 10,000 atoms. HemePLM-Diffuse has features of …

Incomplete Data, Complete Dynamics: A Diffusion Approach
Zihan Zhou, Chenguang Wang, Hongyi Ye, Yongtao Guan, Tianshu Yu
https://arxiv.org/abs/2509.20098 https://

Incomplete Data, Complete Dynamics: A Diffusion Approach
Learning physical dynamics from data is a fundamental challenge in machine learning and scientific modeling. Real-world observational data are inherently incomplete and irregularly sampled, posing significant challenges for existing data-driven approaches. In this work, we propose a principled diffusion-based framework for learning physical systems from incomplete training samples. To this end, our method strategically partitions each such sample into observed context and unobserved query compo…

Peak separation methods for inverse photoelectron spectra: Comparing second derivative, curve fitting, and deconvolution analyses
Ryotaro Nakazawa, Haruki Sato, Hiroyuki Yoshida
https://arxiv.org/abs/2509.21246

Peak separation methods for inverse photoelectron spectra: Comparing second derivative, curve fitting, and deconvolution analyses
Inverse photoelectron spectroscopy (IPES) is a powerful technique for probing the unoccupied electronic states of materials. It can be regarded as the inversion process of photoelectron spectroscopy (PES), which examines the occupied states. Recently developed low-energy inverse photoelectron spectroscopy (LEIPS) can significantly advance the study of unoccupied states, owing to an improved signal-to-noise ratio and minimal sample damage compared to conventional IPES. However, the instrumental …

Distribution Testing in the Presence of Arbitrarily Dominant Noise with Verification Queries
Hadley Black, Christopher Ye
https://arxiv.org/abs/2509.17269 https://

Distribution Testing in the Presence of Arbitrarily Dominant Noise with Verification Queries
We study distribution testing without direct access to a source of relevant data, but rather to one where only a tiny fraction is relevant. To enable this, we introduce the following verification query model. The goal is to perform a statistical task on distribution $\boldsymbol{p}$ given sample access to a mixture $\boldsymbol{r} = λ\boldsymbol{p} + (1-λ)\boldsymbol{q}$ and the ability to query whether a sample was generated by $\boldsymbol{p}$ or by $\boldsymbol{q}$. In general, if $m_0$ sa…

More framework added. Dresser shelf/draws and the closet taking some shape.
The varnish/paint arrived and a test shows it way too dark. Almost black to my eyes in that dark room. So some other sample tins ordered. Hopefully one of them will be closer.

A Dimensional Approach to Canine Bark Analysis for Assistance Dog Seizure Signaling
Hailin Song, Shelley Brady, Tom\'as Ward, Alan F. Smeaton
https://arxiv.org/abs/2509.18375

MINDS: The very low-mass star and brown dwarf sample II. Probing disk settling, dust properties, and dust-gas interplay with JWST/MIRI
Hyerin Jang, Aditya M. Arabhavi, Till Kaeufer, Rens Waters, Inga Kamp, Thomas Henning, Alessio Caratti o Garatti, Ewine F. van Dishoeck, Giulia Perotti, Jayatee Kanwar, Manuel G\"udel, Maria Morales-Calder\'on, Sierra L. Grant, Valentin Christiaens

MINDS: The very low-mass star and brown dwarf sample II. Probing disk settling, dust properties, and dust-gas interplay with JWST/MIRI
Disks around very low-mass stars (VLMS) provide environments for the formation of Earth-like planets. Mid-infrared observations have revealed that these disks exhibit weak silicate features and strong hydrocarbon emissions. This study characterizes the dust properties and geometrical structures of VLMS and brown dwarf (BD) disks, observed by the James Webb Space Telescope (JWST)/Mid-Infrared Instrument (MIRI), and connects these to gas column density and potential evolutionary stages. We analyz…

NFL overreaction Monday: Fishy betting lines and 4 early picks for Week 4 https://www.nytimes.com/athletic/6652260/2025/09/22/nfl-overreaction-monday-week-4-colts-rams-underdogs-betting/

Adaptive Event-Triggered Policy Gradient for Multi-Agent Reinforcement Learning
Umer Siddique, Abhinav Sinha, Yongcan Cao
https://arxiv.org/abs/2509.20338 https://

Adaptive Event-Triggered Policy Gradient for Multi-Agent Reinforcement Learning
Conventional multi-agent reinforcement learning (MARL) methods rely on time-triggered execution, where agents sample and communicate actions at fixed intervals. This approach is often computationally expensive and communication-intensive. To address this limitation, we propose ET-MAPG (Event-Triggered Multi-Agent Policy Gradient reinforcement learning), a framework that jointly learns an agent's control policy and its event-triggering policy. Unlike prior work that decouples these mechanisms, E…

Optimal and Efficient Sample Size Re-estimation: A Dynamic Cost Framework
Rui Jin, Cai Wu, Qiqi Deng
https://arxiv.org/abs/2509.16636 https://arxiv.org/pdf…

Optimal and Efficient Sample Size Re-estimation: A Dynamic Cost Framework
Adaptive sample size re-estimation (SSR) is a well-established strategy for improving the efficiency and flexibility of clinical trials. Its central challenge is determining whether, and by how much, to increase the sample size at an interim analysis. This decision requires a rational framework for balancing the potential gain in statistical power against the risk and cost of further investment. Prevailing optimization approaches, such as the Jennison and Turnbull (JT) method, address this by m…

Tomorrow we have a Symposium at the Advanced Medical BIOimaging core facility #AMBIO of the @… , to celebrate our 10 year anniversary. There will be lots of great talks about microscopy stuff (single-molecule spatial omics, multi scale microscopy, light sheet,…

Probing redshift-dependent systematics in the Hubble tension: Model-independent $H_0$ constraints from DESI R2
Tonghua Liu, Shuo Cao, Jieci Wang
https://arxiv.org/abs/2509.20898

Probing redshift-dependent systematics in the Hubble tension: Model-independent $H_0$ constraints from DESI R2
We present a model-independent determination of the Hubble constant ($H_0$) using the latest observational data from multiple cosmological probes. By combining baryon acoustic oscillation (BAO) measurements from the second data release of the Dark Energy Spectroscopic Instrument (DESI DR2), cosmic chronometer $H(z)$ data, and the Pantheon Plus Type Ia supernova (SN Ia) sample, we reconstruct the cosmic expansion history through Gaussian process regression without assuming a specific cosmologica…

Online Robust Planning under Model Uncertainty: A Sample-Based Approach
Tamir Shazman, Idan Lev-Yehudi, Ron Benchetit, Vadim Indelman
https://arxiv.org/abs/2509.10162 https://…

Online Robust Planning under Model Uncertainty: A Sample-Based Approach
Online planning in Markov Decision Processes (MDPs) enables agents to make sequential decisions by simulating future trajectories from the current state, making it well-suited for large-scale or dynamic environments. Sample-based methods such as Sparse Sampling and Monte Carlo Tree Search (MCTS) are widely adopted for their ability to approximate optimal actions using a generative model. However, in practical settings, the generative model is often learned from limited data, introducing approxi…

Dear Santa, I've been REALLY good this year...
https://www.thermofisher.com/us/en/home/electron-microscopy/products/dualbeam-fib-sem-microscopes/helios-hydra-dualbeam.html

Anchored Langevin Algorithms
Mert Gurbuzbalaban, Hoang M. Nguyen, Xicheng Zhang, Lingjiong Zhu
https://arxiv.org/abs/2509.19455 https://arxiv.org/pdf/2509.…

Anchored Langevin Algorithms
Standard first-order Langevin algorithms such as the unadjusted Langevin algorithm (ULA) are obtained by discretizing the Langevin diffusion and are widely used for sampling in machine learning because they scale to high dimensions and large datasets. However, they face two key limitations: (i) they require differentiable log-densities, excluding targets with non-differentiable components; and (ii) they generally fail to sample heavy-tailed targets. We propose anchored Langevin dynamics, a unif…

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

On The Cutoff Phenomenon For Dyson-Laguerre Processes
Samuel Chan-Ashing (CEREMADE, CMAP)
https://arxiv.org/abs/2509.19798 https://arxiv.org/pdf/2509.19798…

On The Cutoff Phenomenon For Dyson-Laguerre Processes
We study the convergence to equilibrium in high dimensions, focusing on explicit bounds on mixing times and the emergence of the cutoff phenomenon for Dyson-Laguerre processes. These are interacting particle systems with non-constant diffusion coefficients, arising naturally in the context of sample covariance matrices. The infinitesimal generator of the process admits generalized Laguerre orthogonal polynomials as eigenfunctions. Our analysis relies on several distances and divergences, inclu…

SOE: Sample-Efficient Robot Policy Self-Improvement via On-Manifold Exploration
Yang Jin, Jun Lv, Han Xue, Wendi Chen, Chuan Wen, Cewu Lu
https://arxiv.org/abs/2509.19292 https:…

Crosslisted article(s) found for math.ST. https://arxiv.org/list/math.ST/new
[1/1]:
- Sample completion, structured correlation, and Netflix problems
Leonardo N. Coregliano, Maryanthe Malliaris

**"NASA will hold a press conference to discuss an enigmatic Martian rock that contains possible biosignatures.**"
NASA to Make Major Announcement About Martian Rock Sample on Wednesday. Here's How to Watch
https://gizmodo.com/nasa-to-make-major-announcement-about-martian-rock-sample-on-wednesday-heres-how-to-watch-2000655885

MOCLIP: A Foundation Model for Large-Scale Nanophotonic Inverse Design
S. Rodionov, A. Burguete-Lopez, M. Makarenko, Q. Wang, F. Getman, A. Fratalocchi
https://arxiv.org/abs/2511.18980 https://arxiv.org/pdf/2511.18980 https://arxiv.org/html/2511.18980
arXiv:2511.18980v1 Announce Type: new
Abstract: Foundation models (FM) are transforming artificial intelligence by enabling generalizable, data-efficient solutions across different domains for a broad range of applications. However, the lack of large and diverse datasets limits the development of FM in nanophotonics. This work presents MOCLIP (Metasurface Optics Contrastive Learning Pretrained), a nanophotonic foundation model that integrates metasurface geometry and spectra within a shared latent space. MOCLIP employs contrastive learning to align geometry and spectral representations using an experimentally acquired dataset with a sample density comparable to ImageNet-1K. The study demonstrates MOCLIP inverse design capabilities for high-throughput zero-shot prediction at a rate of 0.2 million samples per second, enabling the design of a full 4-inch wafer populated with high-density metasurfaces in minutes. It also shows generative latent-space optimization reaching 97 percent accuracy. Finally, we introduce an optical information storage concept that uses MOCLIP to achieve a density of 0.1 Gbit per square millimeter at the resolution limit, exceeding commercial optical media by a factor of six. These results position MOCLIP as a scalable and versatile platform for next-generation photonic design and data-driven applications.
toXiv_bot_toot

NeuS-QA: Grounding Long-Form Video Understanding in Temporal Logic and Neuro-Symbolic Reasoning
Sahil Shah, S P Sharan, Harsh Goel, Minkyu Choi, Mustafa Munir, Manvik Pasula, Radu Marculescu, Sandeep Chinchali
https://arxiv.org/abs/2509.18041

NeuS-QA: Grounding Long-Form Video Understanding in Temporal Logic and Neuro-Symbolic Reasoning
Long-Form Video Question Answering (LVQA) poses challenges beyond traditional visual question answering (VQA), which is often limited to static images or short video clips. While current vision-language models (VLMs) perform well in those settings, they struggle with complex queries in LVQA over long videos involving multi-step temporal reasoning and causality. Vanilla approaches, which sample frames uniformly and feed them to a VLM with the question, incur significant token overhead, forcing s…

Power Spectral Density Estimation via Universal Truncated Order Statistics Filtering
David Campos Anchieta, John R. Buck
https://arxiv.org/abs/2509.16359 https://

Power Spectral Density Estimation via Universal Truncated Order Statistics Filtering
Loud transient signals in underwater acoustic data increase the bias and variance of background noise power spectral density (PSD) estimates based on sample mean. Recently, two PSD estimators mitigated the loud transient impact on PSD estimates by applying order statistics filtering (OSF). The first, the Schwock and Abadi Welch Percentile, scales a single rank order statistic (OS) of consecutive periodograms. The second, the truncated linear order statistics filter, is a weighted sum of OS up t…

Accounting the size distribution of HTS granules for the critical current density from magnetic measurements
D. M. Gokhfeld, Yu. S. Gokhfeld
https://arxiv.org/abs/2508.17707 htt…

Accounting the size distribution of HTS granules for the critical current density from magnetic measurements
The determination of the critical current density from magnetic hysteresis loops is widely used to characterize and compare superconducting samples. Magnetic hysteresis loops for tapes and single crystals depend on both the critical current density and sample size. The latter sets the scale of supercurrent circulation. However, in polycrystalline high-temperature superconductors prepared by solid-phase synthesis or by sol-gel method, the magnetization is determined by the circulation of supercu…

Polarity inversion line helicities and solar eruptivity
K. Moraitis, J. K. Thalmann
https://arxiv.org/abs/2509.19864 https://arxiv.org/pdf/2509.19864

Polarity inversion line helicities and solar eruptivity
This work examines the relationship between solar eruptivity and the relative helicity that is contained around the polarity inversion line (PIL) of the magnetic field, along with its current-carrying component. To this end, we analyze the evolution of the PIL helicities in a sample of $\sim 40$ solar active regions which exhibited more than 200 flares of class M or higher. The computation of the PIL helicities is accomplished with the help of relative field line helicity, the recently-develope…

Sample-optimal single-copy quantum state tomography via shallow depth measurements
Gyungmin Cho, Dohun Kim
https://arxiv.org/abs/2509.12703 https://arxiv.o…

Sample-optimal single-copy quantum state tomography via shallow depth measurements
Quantum state tomography (QST) is one of the fundamental problems in quantum information. Among various metrics, sample complexity is widely used to evaluate QST algorithms. While multi-copy measurements are known to achieve optimal sample complexity, they are challenging to implement on near-term quantum devices. In practice, single-copy measurements with shallow-depth circuits are more feasible. Although a near-optimal QST algorithm under single-qubit measurements has recently been proposed, …

VLA Observations at 6 and 19 GHz of a Complete Sample of Radio Loud Quasars with redshifts between 2.5 and 5.28: II. Sample definition, radio images, and analysis
John F. C. Wardle, Mark Birkinshaw, Diana M. Worrall, Teddy C. C. Cheung, Doug Gobeille, Daisy Matthews, Jesse Reeves
https://arxiv.org/abs/2509.18380

Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method
Kairong Han, Weidong Huang, Taiyang Zhou, Peng Zhen, Kun Kuang
https://arxiv.org/abs/2509.18148 …

Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method
In the online ride-hailing pricing context, companies often conduct randomized controlled trials (RCTs) and utilize uplift models to assess the effect of discounts on customer orders, which substantially influences competitive market outcomes. However, due to the high cost of RCTs, the proportion of trial data relative to observational data is small, which only accounts for 0.65\% of total traffic in our context, resulting in significant bias when generalizing to the broader user base. Addition…

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…

A more efficient method for large-sample model-free feature screening via multi-armed bandits
Xiaxue Ouyang, Xinlai Kang, Mengyu Li, Zhenxing Dou, Jun Yu, Cheng Meng
https://arxiv.org/abs/2509.16085

A more efficient method for large-sample model-free feature screening via multi-armed bandits
We consider the model-free feature screening in large-scale ultrahigh-dimensional data analysis. Existing feature screening methods often face substantial computational challenges when dealing with large sample sizes. To alleviate the computational burden, we propose a rank-based model-free sure independence screening method (CR-SIS) and its efficient variant, BanditCR-SIS. The CR-SIS method, based on Chatterjee's rank correlation, is as straightforward to implement as the sure independence scr…

Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds
Remo Sasso, Michelangelo Conserva, Dominik Jeurissen, Paulo Rauber
https://arxiv.org/abs/2509.15915

Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds
While reinforcement learning from scratch has shown impressive results in solving sequential decision-making tasks with efficient simulators, real-world applications with expensive interactions require more sample-efficient agents. Foundation models (FMs) are natural candidates to improve sample efficiency as they possess broad knowledge and reasoning capabilities, but it is yet unclear how to effectively integrate them into the reinforcement learning framework. In this paper, we anticipate and…

Analyzing and improving a classical Betti number estimation algorithm
Julien Sorci
https://arxiv.org/abs/2509.16171 https://arxiv.org/pdf/2509.16171…

Analyzing and improving a classical Betti number estimation algorithm
Recently, a classical algorithm for estimating the normalized Betti number of an arbitrary simplicial complex was proposed. Motivated by a quantum algorithm with a similar Monte Carlo structure and improved sample complexity, we give a more in-depth analysis of the sample complexity of this classical algorithm. To this end, we present bounds for the variance of the estimators used in the classical algorithm and show that the variance depends on certain combinatorial properties of the underlying…

MIDIS: Unveiling the Star Formation History in massive galaxies at $1<z<4.5$ with spectro-photometric analysis
M. Annunziatella, P. G. P\'erez-Gonz\'alez, J. \'Alvarez-M\'arquez, L. Costantin, E. Iani, \'A. Labiano, P. Rinaldi, L. Boogaard, R. A. Meyer, G. \"Ostlin, L. Colina, J. Melinder, I. Jermann, S. Gillman, D. Langeroodi, J. Hjorth, A. Alonso-Herrero, A. Eckart, F. Walter, P. P. van der Werf, A. Bik, F. Pei{\ss}ker, K. I. Caputi, M. Garc\'ia-Mar…

MIDIS: Unveiling the Star Formation History in massive galaxies at $1
We investigate the star formation histories (SFHs) of a sample of massive galaxies ($M_\star \geq 10^{10} \, M_\odot$) in the redshift range $1 < z < 4.5$. We analyze spectro-photometric data combining broadband photometry from HST and JWST with low-resolution grism spectroscopy from JWST/NIRISS, obtained as part of the MIDIS (MIRI Deep Imaging Survey) program. SFHs are derived through spectral energy distribution (SED) fitting using two independent codes, BAGPIPES and Synthesizer, under variou…