Tootfinder

Playbook: Trump, Iran and the known unknown (Zack Stanton/Politico)
https://www.politico.com/newsletters/playbook/2025/06/22/trump-iran-and-the-known-unknown-00417199
http://www.memeorandum.com/250622/p52#a250622p52

On Continuous Monitoring of Risk Violations under Unknown Shift
Alexander Timans, Rajeev Verma, Eric Nalisnick, Christian A. Naesseth
https://arxiv.org/abs/2506.16416

On Continuous Monitoring of Risk Violations under Unknown Shift
Machine learning systems deployed in the real world must operate under dynamic and often unpredictable distribution shifts. This challenges the validity of statistical safety assurances on the system's risk established beforehand. Common risk control frameworks rely on fixed assumptions and lack mechanisms to continuously monitor deployment reliability. In this work, we propose a general framework for the real-time monitoring of risk violations in evolving data streams. Leveraging the 'testing …

wordnet: WordNet relationships
A network of English words from the WordNet. Node is a word, and edge denotes relationships between words (synonymy, hyperonymy, meronymy, etc.). The date at which this network was extracted from WordNet is not unknown.
This network has 146005 nodes and 656999 edges.
Tags: Informational, Language, Unweighted
htt…

Chaotic? Yes. Evil? Sometimes. All panels displaying too few screens? Hell yes.
https://vis.social/@infobeautiful/114557722686209992

Las Vegas Raiders Insider: Player With Unknown Future Was Secret Standout at Minicamp https://heavy.com/sports/nfl/las-vegas-raiders/player-unknown-future-secret-standout-minicamp/?adt_ei=[email]

Quantum Advantage in Learning Quantum Dynamics via Fourier coefficient extraction
Alice Barthe, Mahtab Yaghubi Rad, Michele Grossi, Vedran Dunjko
https://arxiv.org/abs/2506.17089 …

Quantum Advantage in Learning Quantum Dynamics via Fourier coefficient extraction
One of the key challenges in quantum machine learning is finding relevant machine learning tasks with a provable quantum advantage. A natural candidate for this is learning unknown Hamiltonian dynamics. Here, we tackle the supervised learning version of this problem, where we are given random examples of the inputs to the dynamics as classical data, paired with the expectation values of some observable after the time evolution, as corresponding output labels. The task is to replicate the corres…

That Zohran Kwame Mamdani should be a serious contender for the leadership of America’s largest city is both a sign of the times and of his individual capabilities.
Polls show him within striking distance of the frontrunner Andrew Cuomo in what is now essentially a two-horse race, with Brad Lander trailing a distant third.
Mamdani came to the US aged seven from Uganda where he was born to parents of Indian descent.
His father is a political scientist Mahmood Mamdani, and hi…

Code Rate Optimization via Neural Polar Decoders
Ziv Aharoni, Bashar Huleihel, Henry D Pfister, Haim H Permuter
https://arxiv.org/abs/2506.15836 https://…

Code Rate Optimization via Neural Polar Decoders
This paper proposes a method to optimize communication code rates via the application of neural polar decoders (NPDs). Employing this approach enables simultaneous optimization of code rates over input distributions while providing a practical coding scheme within the framework of polar codes. The proposed approach is designed for scenarios where the channel model is unknown, treating the channel as a black box that produces output samples from input samples. We employ polar codes to achieve ou…

🇺🇦 #NowPlaying on KEXP's #SoundsOfSurvivance
Unknown Mortal Orchestra:
🎵 ONE HUNDRED BATS
#UnknownMortalOrchestra
#newRelease 🆕 single
https://unknown-mortal-orchestra.bandcamp.com/track/one-hundred-bats
https://open.spotify.com/track/5hdrbks3ryBnWAtYXSlMdf

Analytic Full Potential Adjoint Solution for Two-dimensional Subcritical Flows
Carlos Lozano, Jorge Ponsin
https://arxiv.org/abs/2506.16886 https://…

Analytic Full Potential Adjoint Solution for Two-dimensional Subcritical Flows
We investigate the analytic adjoint solution of the two-dimensional (2D) full potential equation for subcritical flows for a cost function measuring aerodynamic force by the Green's function approach and by the connection of the adjoint full potential and compressible Euler equations. The solution for aerodynamic lift is written in terms of two unknown functions encoding the effect of perturbations to the Kutta condition. We analyze the properties of these functions from an analytic viewpoint a…

Large-amplitude periodic solutions to the steady Euler equations with piecewise constant vorticity
Alex Doak, Karsten Matthies, Jonathan Sewell, Miles H. Wheeler
https://arxiv.org/abs/2506.17002

Large-amplitude periodic solutions to the steady Euler equations with piecewise constant vorticity
We consider steady solutions to the incompressible Euler equations in a two-dimensional channel with rigid walls. The flow consists of two periodic layers of constant vorticity separated by an unknown interface. Using global bifurcation theory, we rigorously construct curves of solutions that terminate either with stagnation on the interface or when the conformal equivalence between one of the layers and a strip breaks down in a $C^1$ sense. We give numerical evidence that, depending on paramet…

Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic Generation
Chenxu Wang, Yonggang Jin, Cheng Hu, Youpeng Zhao, Zipeng Dai, Jian Zhao, Shiyu Huang, Liuyu Xiang, Junge Zhang, Zhaofeng He
https://arxiv.org/abs/2506.16718

Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic Generation
Adapting a single agent to a new multi-agent system brings challenges, necessitating adjustments across various tasks, environments, and interactions with unknown teammates and opponents. Addressing this challenge is highly complex, and researchers have proposed two simplified scenarios, Multi-agent reinforcement learning for zero-shot learning and Ad-Hoc Teamwork. Building on these foundations, we propose a more comprehensive setting, Agent Collaborative-Competitive Adaptation (ACCA), which ev…

– #blogwochen2025

Erstmals wurden Tiefsee-#Seespinnen entdeckt, die mithilfe von #Methan-basierten #Bakterien überleben.
Sie haben anscheinend auch von

First methane-powered sea spiders found crawling on the ocean floor
Scientists on the US West Coast say they discovered three previously unknown species of deep-sea spider that could have a rare diet fueled by a common greenhouse gas.

chicago_road: Chicago road network
A transportation network of Chicago, USA, from an unknown date (probably late 20th century). Nodes represent intersections or endpoints and edge represent the road connecting these nodes.
This network has 12982 nodes and 39018 edges.
Tags: Transportation, Roads, Unweighted
https://

That Zohran Kwame Mamdani should be a serious contender for the leadership of America’s largest city is both a sign of the times and of his individual capabilities.
Polls show him within striking distance of the frontrunner Andrew Cuomo in what is now essentially a two-horse race, with Lander trailing a distant third.
Mamdani came to the US aged seven from Uganda where he was born to parents of Indian descent.
His father is a political scientist Mahmood Mamdani, and his mot…

Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places
Xinglei Wang, Tao Cheng, Stephen Law, Zichao Zeng, Ilya Ilyankou, Junyuan Liu, Lu Yin, Weiming Huang, Natchapon Jongwiriyanurak
https://arxiv.org/abs/2506.14070…

Into the Unknown: Applying Inductive Spatial-Semantic Location Embeddings for Predicting Individuals' Mobility Beyond Visited Places
Predicting individuals' next locations is a core task in human mobility modelling, with wide-ranging implications for urban planning, transportation, public policy and personalised mobility services. Traditional approaches largely depend on location embeddings learned from historical mobility patterns, limiting their ability to encode explicit spatial information, integrate rich urban semantic context, and accommodate previously unseen locations. To address these challenges, we explore the appl…

Beating solitons with nonzero relative wavenumber, their interaction, and coexistence with Akhmediev breathers
Wen-Juan Che, Chong Liu
https://arxiv.org/abs/2506.16989

Beating solitons with nonzero relative wavenumber, their interaction, and coexistence with Akhmediev breathers
We study beating solitons and their interaction for the three-component nonlinear Schrödinger equations (NLSEs) in both focusing and defocusing cases. We identify a previously unknown family of beating solitons with nonzero relative wavenumber which is absent in the two-component NLSEs. Existence diagrams of these beating solitons are extracted from the exact solutions. Unique coexistence and interaction between beating solitons and vector Akhmediev breathers are revealed by using the existenc…

Calamus 35 To you of New England
Honestly I find this Whitman entreaty to national unity kind of tedious. It's charming and American but it's just so earnest. And this poem doesn't have much music.
Stretching for a gay reading...
a superb friendship, exalté, previously unknown,
... it waits ... latent in all men.
Once again his calls for unity are partly rooted in relationships between men: "friendship" here, the least sexual of his words. But it's also a sort of hidden connection, unknown, latent, and that's a little queer-coded to me.

residence_hall: ANU Residence Hall network
A network of friendships among students living in a residence hall at Australian National University (date unknown). Edge direction indicates that resident i named resident j as a friend, and edge weight indicates the level of friendship: 5 (best friend), 4 (close friend), 3 (friend), 2, 1.
This network has 217 nodes and 2672 edges.
Tags: Social, Offline, Weighted

While technically a correct fix, this #dotnet fix is about to break a lot of deployments. This was just deployed in the latest release of .NET 8 and 9.
https://github.com/dotnet/aspnetcore/p

[release/8.0] Forwarded Headers Middleware: Ignore XForwardedHeaders from Unknown Proxy by github-actions[bot] · Pull Request #61623 · dotnet/aspnetcore
Backport of #61530 to release/8.0 /cc @BrennanConroy @yannic-hamann-abb Forwarded Headers Middleware: Ignore XForwardedHeaders from Unknown Proxy Description If the ForwardedHeadersMiddleware middl...

H\"older continuity of Minimizing $W^{s,p}$-Harmonic Maps
Akshara Vincent
https://arxiv.org/abs/2506.16442 https://arxiv.org/pdf…

Hölder continuity of Minimizing $W^{s,p}$-Harmonic Maps
We show that the mappings $u\in \dot{W}^{s,p}(\mathbb{R}^n,\mathcal{N})$ into manifolds $\mathcal{N}$ of a sufficiently simple topology that minimize the energy $$\int_{\mathbb{R}^n}\int_{\mathbb{R}^n}\frac{|u(x)-u(y)|^p}{|x-y|^{n+sp}} \;dx\;dy$$ are locally Hölder continuous in a bounded domain $Ω$ outside a singular set $Σ$ with Hausdorff dimension strictly smaller than $n-sp$. We avoid the use of a monotonicity formula (which is unknown if $p \neq 2$) by using a blow-u…

Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework
Michael Ledford, William Regli
https://arxiv.org/abs/2506.15856 …

Learning to Coordinate Under Threshold Rewards: A Cooperative Multi-Agent Bandit Framework
Cooperative multi-agent systems often face tasks that require coordinated actions under uncertainty. While multi-armed bandit (MAB) problems provide a powerful framework for decentralized learning, most prior work assumes individually attainable rewards. We address the challenging setting where rewards are threshold-activated: an arm yields a payoff only when a minimum number of agents pull it simultaneously, with this threshold unknown in advance. Complicating matters further, some arms are de…

Varanus: Runtime Verification for CSP
Matt Luckcuck, Angelo Ferrando, Fatma Faruq
https://arxiv.org/abs/2506.14426 https://arxiv.org/…

Varanus: Runtime Verification for CSP
Autonomous systems are often used in changeable and unknown environments, where traditional verification may not be suitable. Runtime Verification (RV) checks events performed by a system against a formal specification of its intended behaviour, making it highly suitable for ensuring that an autonomous system is obeying its specification at runtime. Communicating Sequential Processes (CSP) is a process algebra usually used in static verification, which captures behaviour as a trace of events, m…

🇺🇦 #NowPlaying on BBCRadio3's #NightTracks
Angeline Morrison:
🎵 Unknown African Boy (d. 1830)
#AngelineMorrison
https://open.spotify.com/track/5TNvxVT2KhvZMKjY5zGeRg

🇺🇦 Auf radioeins läuft...
Unknown Mortal Orchestra:
🎵 Multi-Love
#NowPlaying #UnknownMortalOrchestra
https://facundomohrr.bandcamp.com/track/unknown-mortal-orchestra-multi-love-facundo-mohrr-remix
https://open.spotify.com/track/1XKAeevAbxSSMuTcRT0APS

Single Index Bandits: Generalized Linear Contextual Bandits with Unknown Reward Functions
Yue Kang, Mingshuo Liu, Bongsoo Yi, Jing Lyu, Zhi Zhang, Doudou Zhou, Yao Li
https://arxiv.org/abs/2506.12751

Single Index Bandits: Generalized Linear Contextual Bandits with Unknown Reward Functions
Generalized linear bandits have been extensively studied due to their broad applicability in real-world online decision-making problems. However, these methods typically assume that the expected reward function is known to the users, an assumption that is often unrealistic in practice. Misspecification of this link function can lead to the failure of all existing algorithms. In this work, we address this critical limitation by introducing a new problem of generalized linear bandits with unknown…

Recent Advances and Future Directions in Literature-Based Discovery
Andrej Kastrin, Bojan Cestnik, Nada Lavra\v{c}
https://arxiv.org/abs/2506.12385 https:/…

Recent Advances and Future Directions in Literature-Based Discovery
The explosive growth of scientific publications has created an urgent need for automated methods that facilitate knowledge synthesis and hypothesis generation. Literature-based discovery (LBD) addresses this challenge by uncovering previously unknown associations between disparate domains. This article surveys recent methodological advances in LBD, focusing on developments from 2000 to the present. We review progress in three key areas: knowledge graph construction, deep learning approaches, an…

Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching
Giacomo Meanti, Thomas Ryckeboer, Michael Arbel, Julien Mairal
https://arxiv.org/abs/2506.14605

Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching
This work addresses image restoration tasks through the lens of inverse problems using unpaired datasets. In contrast to traditional approaches -- which typically assume full knowledge of the forward model or access to paired degraded and ground-truth images -- the proposed method operates under minimal assumptions and relies only on small, unpaired datasets. This makes it particularly well-suited for real-world scenarios, where the forward model is often unknown or misspecified, and collecting…

Sonnet 117 - CXVII
Accuse me thus: that I have scanted all,
Wherein I should your great deserts repay,
Forgot upon your dearest love to call,
Whereto all bonds do tie me day by day;
That I have frequent been with unknown minds,
And given to time your own dear-purchased right;
That I have hoisted sail to all the winds
Which should transport me farthest from your sight.
Book both my wilfulness and errors down,
And on just proof surmis…

This https://arxiv.org/abs/2412.13664 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

A Skeleton-Based Topological Planner for Exploration in Complex Unknown Environments
The capability of autonomous exploration in complex, unknown environments is important in many robotic applications. While recent research on autonomous exploration have achieved much progress, there are still limitations, e.g., existing methods relying on greedy heuristics or optimal path planning are often hindered by repetitive paths and high computational demands. To address such limitations, we propose a novel exploration framework that utilizes the global topology information of observed …

One of the reasons that ICE can't entirely get away with the whole masking thing is that there was a guy who sued because 5 unknown (to him) DEA agents busted in to his house without a warrant and beat and threatened him and his family.
Positive, specific identification isn't necessary, IOW.

1. To continue using this software/device you must update the firmware.
2. Download update.
3. Try to install update.
4. An unknown error occurred.
5. Go to 1.

Bayesian Inference for Initial Heat States with Gaussian Series Priors
Matteo Giordano
https://arxiv.org/abs/2506.14241 https://arxiv…

Bayesian Inference for Initial Heat States with Gaussian Series Priors
We consider the statistical linear inverse problem of recovering the unknown initial heat state from noisy interior measurements over an inhomogeneous domain of the solution to the heat equation at a fixed time instant. We employ nonparametric Bayesian procedures with Gaussian series priors defined on the Dirichlet-Laplacian eigenbasis, yielding convenient conjugate posterior distributions with explicit expressions for posterior inference. We review recent theoretical results that provide asymp…

Reddit Daily Digest is, probably not surprising for many other than me, NOT a digest of the subreddits I’m subscribed to.
It’s shit selected automatically based on unknown rules that Reddit hopes to pull me on the site.
On my side, the result is instant unsubscribe. And sharing so others can avoid this crap.

DATA-DRIVEN PRONTO: a Model-free Solution for Numerical Optimal Control
Marco Borghesi, Lorenzo Sforni, Giuseppe Notarstefano
https://arxiv.org/abs/2506.15465

DATA-DRIVEN PRONTO: a Model-free Solution for Numerical Optimal Control
This article addresses the problem of data-driven numerical optimal control for unknown nonlinear systems. In our scenario, we suppose to have the possibility of performing multiple experiments (or simulations) on the system. Experiments are performed by relying on a data-driven tracking controller able to steer the system towards a desired reference. Our proposed DATA-DRIVEN PRONTO algorithm iteratively refines a tentative solution of the optimal control problem by computing an approximate des…

A Quantum Annealing Approach for Solving Optimal Feature Selection and Next Release Problems
Shuchang Wang, Xiaopeng Qiu, Yingxing Xue, Yanfu Li, Wei Yang
https://arxiv.org/abs/2506.14129

A Quantum Annealing Approach for Solving Optimal Feature Selection and Next Release Problems
Search-based software engineering (SBSE) addresses critical optimization challenges in software engineering, including the next release problem (NRP) and feature selection problem (FSP). While traditional heuristic approaches and integer linear programming (ILP) methods have demonstrated efficacy for small to medium-scale problems, their scalability to large-scale instances remains unknown. Here, we introduce quantum annealing (QA) as a subroutine to tackling multi-objective SBSE problems, leve…

Can you see how I learn? Human observers' inferences about Reinforcement Learning agents' learning processes
Bernhard Hilpert, Muhan Hou, Kim Baraka, Joost Broekens
https://arxiv.org/abs/2506.13583

Can you see how I learn? Human observers' inferences about Reinforcement Learning agents' learning processes
Reinforcement Learning (RL) agents often exhibit learning behaviors that are not intuitively interpretable by human observers, which can result in suboptimal feedback in collaborative teaching settings. Yet, how humans perceive and interpret RL agent's learning behavior is largely unknown. In a bottom-up approach with two experiments, this work provides a data-driven understanding of the factors of human observers' understanding of the agent's learning process. A novel, observation-based paradi…

Determining the chemical potential via universal density functional learning
Florian Samm\"uller, Matthias Schmidt
https://arxiv.org/abs/2506.15608 ht…

Determining the chemical potential via universal density functional learning
We demonstrate that the machine learning of density functionals allows one to determine simultaneously the equilibrium chemical potential across simulation datasets of inhomogeneous classical fluids. Minimization of an implicit loss function based on an Euler-Lagrange equation yields both the universal one-body direct correlation functional, which is represented locally by a neural network, as well as the system-specific unknown chemical potential values. The method can serve as an efficient al…

Tractable Graph Structures in EFX Orientation
V\'aclav Bla\v{z}ej, Sushmita Gupta, M. S. Ramanujan, Peter Strulo
https://arxiv.org/abs/2506.15379 https…

Tractable Graph Structures in EFX Orientation
Since its introduction, envy-freeness up to any good (EFX) has become a fundamental solution concept in fair division of indivisible goods. Its existence remains elusive -- even for four agents with additive utility functions, it is unknown whether an EFX allocation always exists. Unsurprisingly, restricted settings to delineate tractable and intractable cases have been explored. Christadolou, Fiat et al.[EC'23] introduced the notion of EFX-orientation, where the agents form the vertices of a g…

Since watching "A Complete Unknown" I've got right into Joan Baez. What a voice!

On the Robustness of Derivative-free Methods for Linear Quadratic Regulator
Weijian Li, Panagiotis Kounatidis, Zhong-Ping Jiang, Andreas A. Malikopoulos
https://arxiv.org/abs/2506.12596

On the Robustness of Derivative-free Methods for Linear Quadratic Regulator
Policy optimization has drawn increasing attention in reinforcement learning, particularly in the context of derivative-free methods for linear quadratic regulator (LQR) problems with unknown dynamics. This paper focuses on characterizing the robustness of derivative-free methods for solving an infinite-horizon LQR problem. To be specific, we estimate policy gradients by cost values, and study the effect of perturbations on the estimations, where the perturbations may arise from function approx…

Must have this T-shirt. Spotted on unknown guy in Prague.

Intense Hard X-ray Emissions in C-class Flares: A Statistical Study with ASO-S/HXI Data
Changxue Chen, Yang Su, Wei Chen, Jingwei Li, Fu Yu, Weiqun Gan
https://arxiv.org/abs/2506.12294

Intense Hard X-ray Emissions in C-class Flares: A Statistical Study with ASO-S/HXI Data
In the standard model of solar eruptive events, coronal mass ejections (CMEs) and flares are associated with each other through magnetic reconnection initiated by erupting flux ropes. Observations also reveal an increasing association ratio between flares and CMEs with flare intensity. However, the fundamental relationship between flares and CMEs, and that between thermal and nonthermal processes, remains unknown. Here we investigate energetic C-class flares (ECFs) -- Geostationary Operational …

Semi-Blind Channel Estimation for Downlink Communications Based on Dynamic Metasurface Antennas
Amarilton L. Magalh\~aes, Andr\'e L. F. de Almeida, A. Lee Swindlehurst
https://arxiv.org/abs/2506.12639

Semi-Blind Channel Estimation for Downlink Communications Based on Dynamic Metasurface Antennas
Dynamic metasurface antennas (DMAs) are emerging as a promising technology to enable energy-efficient, large array-based multi-antenna systems. This paper presents a simple channel estimation scheme for the downlink of a multiple-input single-output orthogonal frequency division multiplexing (MISO-OFDM) communication system exploiting DMAs. The proposed scheme extracts separate estimates of the wireless channel and the unknown waveguide propagation vector using a simple iterative algorithm base…

This man has been a legal permanent resident of the United States for 10 years. He was at his interview to finalize his US citizenship when he was instead carried away in handcuffs to an unknown location.
None of his friends or family knows where he has been taken.
He has been charged with no crime.
#MohsenMahdawi

Palestinian Columbia University student arrested by ICE in Vt., attorneys say
Mohsen Mahdawi, a legal permanent resident who has held a green card since 2015, was detained at the U.S. Citizenship and Immigration Services office in…

🇺🇦 #NowPlaying on #BBC6Music's #LaurenLaverne
Unknown Mortal Orchestra:
🎵 That Life
#UnknownMortalOrchestra
https://unknown-mortal-orchestra.bandcamp.com/track/that-life
https://open.spotify.com/track/0M2hckQzSt0AZFytuTC2Hp

Convergence of generalized cross-validation with applications to ill-posed integral equations
Tim Jahn, Mikhail Kirilin
https://arxiv.org/abs/2506.14558 ht…

Convergence of generalized cross-validation with applications to ill-posed integral equations
In this article, we rigorously establish the consistency of generalized cross-validation as a parameter-choice rule for solving inverse problems. We prove that the index chosen by leave-one-out GCV achieves a non-asymptotic, order-optimal error bound with high probability for polynomially ill-posed compact operators. Hereby it is remarkable that the unknown true solution need not satisfy a self-similarity condition, which is generally needed for other heuristic parameter choice rules. We quanti…

Accurate and scalable exchange-correlation with deep learning
Giulia Luise, Chin-Wei Huang, Thijs Vogels, Derk P. Kooi, Sebastian Ehlert, Stephanie Lanius, Klaas J. H. Giesbertz, Amir Karton, Deniz Gunceler, Megan Stanley, Wessel P. Bruinsma, Lin Huang, Xinran Wei, Jos\'e Garrido Torres, Abylay Katbashev, B\'alint M\'at\'e, S\'ekou-Oumar Kaba, Roberto Sordillo, Yingrong Chen, David B. Williams-Young, Christopher M. Bishop, Jan Hermann, Rianne van den Berg, Paola Gor…

Accurate and scalable exchange-correlation with deep learning
Density Functional Theory (DFT) is the most widely used electronic structure method for predicting the properties of molecules and materials. Although DFT is, in principle, an exact reformulation of the Schrödinger equation, practical applications rely on approximations to the unknown exchange-correlation (XC) functional. Most existing XC functionals are constructed using a limited set of increasingly complex, hand-crafted features that improve accuracy at the expense of computational efficien…

🇺🇦 #NowPlaying on KEXP's #EasternEchoes
Unknown Mortal Orchestra:
🎵 The Garden
#UnknownMortalOrchestra
https://unknown-mortal-orchestra.bandcamp.com/track/the-garden
https://open.spotify.com/track/0xUeLKG6g1vGXSlHDsLKAf

Optimal experiment design for practical parameter identifiability and model discrimination
Yue Liu (University of Oxford, Purdue University), Philip K. Maini (University of Oxford), Ruth E. Baker (University of Oxford)
https://arxiv.org/abs/2506.11311

Optimal experiment design for practical parameter identifiability and model discrimination
Mechanistic mathematical models of biological systems usually contain a number of unknown parameters whose values need to be estimated from available experimental data in order for the models to be validated and used to make quantitative predictions. This requires that the models are practically identifiable, that is, the values of the parameters can be confidently determined, given available data. A well-designed experiment can produce data that are much more informative for the purpose of inf…

Into the Unknown: From Structure to Disorder in Protein Function Prediction
{\DJ}esika Kolari\'c, Chi Fung Willis Chow, Rita Zi Zhu, Agnes Toth-Petroczy, T. Reid Alderson, Iva Priti\v{s}anac
https://arxiv.org/abs/2506.06004

Into the Unknown: From Structure to Disorder in Protein Function Prediction
Intrinsically disordered regions (IDRs) account for one-third of the human proteome and play essential biological roles. However, predicting the functions of IDRs remains a major challenge due to their lack of stable structures, rapid sequence evolution, and context-dependent behavior. Many predictors of protein function neglect or underperform on IDRs. Recent advances in computational biology and machine learning, including protein language models, alignment-free approaches, and IDR-specific m…

Details from Ashley Parker and Michael Scherer’s study of Trump’s cellphone habits have a way of lingering in the mind.
The president’s personal number is “broadly circulated.”
He picks up calls from unknown numbers, and keeps a photograph of his own face on his lock screen.
The Cellphone in Chief is a “portal,” Parker and Scherer write,
but it’s also a mirror, a security blanket, and a vulnerability.
Their short psychological study suggests a man who is occasio…

An Easily Tunable Approach to Robust and Sparse High-Dimensional Linear Regression
Takeyuki Sasai, Hironori Fujisawa
https://arxiv.org/abs/2506.12591 https…

An Easily Tunable Approach to Robust and Sparse High-Dimensional Linear Regression
Sparse linear regression methods such as Lasso require a tuning parameter that depends on the noise variance, which is typically unknown and difficult to estimate in practice. In the presence of heavy-tailed noise or adversarial outliers, this problem becomes more challenging. In this paper, we propose an estimator for robust and sparse linear regression that eliminates the need for explicit prior knowledge of the noise scale. Our method builds on the Huber loss and incorporates an iterative sc…

As famous as the unknown soldier.

Good, Bad, Wild Card: PFF's review of Cowboys' roster telling story with unknown finish https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/05/31/how-do-the-cowboys-stack-up-…

Labelling Data with Unknown References
Adrian de Wynter
https://arxiv.org/abs/2506.03083 https://arxiv.org/pdf/2506.03083

Labelling Data with Unknown References
An evaluator is trustworthy when there exists some agreed-upon way to measure its performance as a labeller. The two ways to establish trustworthiness are either by testing it, or by assuming the evaluator `knows' somehow the way to label the corpus. However, if labelled references (e.g., a development set) are unavailable, neither of these approaches work: the former requires the data, and the latter is an assumption, not evidence. To address this, we introduce an algorithm (the `No-Data Algor…

Comparing the Space Densities of Millisecond-Spin Magnetars and Fast X-Ray Transients
Sumedha Biswas, Peter G. Jonker, M. Coleman Miller, Andrew Levan, Jonathan Quirola-V\'asquez
https://arxiv.org/abs/2506.11676

Comparing the Space Densities of Millisecond-Spin Magnetars and Fast X-Ray Transients
Fast X-ray transients (FXTs) are bright X-ray flashes with durations of minutes to hours, peak isotropic luminosities of L_X,peak ~ 10^42-10^47 erg/s, and total isotropic energies of E ~ 10^47-10^50 erg. They have been detected in the soft X-ray band by Chandra, XMM-Newton, Swift-XRT, and, most recently, by Einstein Probe, which has reported more than 50 FXTs in its first year of operation. While several models have been proposed, the nature of many FXTs remains unknown. One model suggests FXTs…

ambassador: Philippines Ambassador bombing (2000)
A temporal network representing snapshots of relationships among individuals directly or indirectly associated with Philippines Ambassador Residence Bombing 2000, Jakarta. Nodes are people, and an edge exists if they are associated with each other. Definition of the edge weight is unknown.
This network has 16 nodes and 13 edges.
Tags: Social, Offline, Weighted, Temporal

Cardinalities in proofreading
Martin Klazar
https://arxiv.org/abs/2506.11358 https://arxiv.org/pdf/2506.11358

Cardinalities in proofreading
In 1975, G. Pólya pointed out that if two proofreaders found $a$, resp. $b$, errors in text, and both found $c$ errors, then the unknown number $e$ of all errors is approximated by $e\approx\frac{ab}{c}$. We devise a realistic combinatorial model of Pólya's result and estimate its performance by the Probabilistic Method.

Impact of improved energy resolution on DUNE sensitivity in presence of a light sterile neutrino
Sabila Parveen, Jogesh Rout, Poonam Mehta
https://arxiv.org/abs/2506.10767

Impact of improved energy resolution on DUNE sensitivity in presence of a light sterile neutrino
The Deep Underground Neutrino Experiment (DUNE) primarily aims to measure the yet unknown parameters of the standard three neutrino framework, i.e., the determination of Dirac CP phase ($δ_{13}$), neutrino mass hierarchy (MH) and octant of $θ_{23}$. In the present work, we consider the standard three neutrino paradigm (referred to as the $(3+0)$ case) and beyond with an additional light sterile neutrino (referred to as the $(3+1)$ case). We consider two configurations : standard energy resolu…

A Random Matrix Theory of Pauli Tomography
Nathan Keenan, John Goold, Alex Nico-Katz
https://arxiv.org/abs/2506.12010 https://arxiv.o…

A Random Matrix Theory of Pauli Tomography
Quantum state tomography (QST), the process of reconstructing some unknown quantum state $\hatρ$ from repeated measurements on copies of said state, is a foundationally important task in the context of quantum computation and simulation. For this reason, a detailed characterization of the error $Δ\hatρ= \hatρ-\hatρ^\prime$ in a QST reconstruction $\hatρ^\prime$ is of clear importance to quantum theory and experiment. In this work, we develop a fully random matrix theory (RMT) treatment of…

GPS Spoofing Attacks on AI-based Navigation Systems with Obstacle Avoidance in UAV
Ji Hyuk Jung, Mi Yeon Hong, Ji Won Yoon
https://arxiv.org/abs/2506.08445

GPS Spoofing Attacks on AI-based Navigation Systems with Obstacle Avoidance in UAV
Recently, approaches using Deep Reinforcement Learning (DRL) have been proposed to solve UAV navigation systems in complex and unknown environments. However, despite extensive research and attention, systematic studies on various security aspects have not yet been conducted. Therefore, in this paper, we conduct research on security vulnerabilities in DRL-based navigation systems, particularly focusing on GPS spoofing attacks against the system. Many recent basic DRL-based navigation systems fun…

winget upgrade --all --include-unknown

Counterexample-Guided Synthesis of Robust Discrete-Time Control Barrier Functions
Erfan Shakhesi, Alexander Katriniok, W. P. M. H. Heemels
https://arxiv.org/abs/2506.13011

Counterexample-Guided Synthesis of Robust Discrete-Time Control Barrier Functions
Learning-based methods have gained popularity for training candidate Control Barrier Functions (CBFs) to satisfy the CBF conditions on a finite set of sampled states. However, since the CBF is unknown a priori, it is unclear which sampled states belong to its zero-superlevel set and must satisfy the CBF conditions, and which ones lie outside it. Existing approaches define a set in which all sampled states are required to satisfy the CBF conditions, thus introducing conservatism. In this paper, …

The Raiders' Many Unknowns Make Them Exciting Heading into 2025 https://www.si.com/nfl/raiders/chip-kelly-las-vegas-eric-stokes-isaiah-pola-mao

Adaptive Data Augmentation for Thompson Sampling
Wonyoung Kim
https://arxiv.org/abs/2506.14479 https://arxiv.org/pdf/2506.14479

Adaptive Data Augmentation for Thompson Sampling
In linear contextual bandits, the objective is to select actions that maximize cumulative rewards, modeled as a linear function with unknown parameters. Although Thompson Sampling performs well empirically, it does not achieve optimal regret bounds. This paper proposes a nearly minimax optimal Thompson Sampling for linear contextual bandits by developing a novel estimator with the adaptive augmentation and coupling of the hypothetical samples that are designed for efficient parameter learning. …

🇺🇦 #NowPlaying on KEXP's #AstralPlane
Unknown Mortal Orchestra:
🎵 FFunny FFrends
#UnknownMortalOrchestra
https://unknown-mortal-orchestra.bandcamp.com/track/ffunny-ffrends-2
https://open.spotify.com/track/49vzuiR9YheTFslIuO4JRV

A Generalized Framework for Approximate Co-Sufficient Sampling
Jie Xie, Dongming Huang
https://arxiv.org/abs/2506.12334 https://arxiv…

A Generalized Framework for Approximate Co-Sufficient Sampling
Approximate co-sufficient sampling (aCSS) offers a principled route to hypothesis testing when null distributions are unknown, yet current implementations are confined to maximum likelihood estimators with smooth or linear regularization and provide little theoretical insight into power. We present a generalized framework that widens the scope of the aCSS method to embrace nonlinear regularization, such as group lasso and nonconvex penalties, as well as robust and nonparametric estimators. More…

Online-Optimized Gated Radial Basis Function Neural Network-Based Adaptive Control
Mingcong Li
https://arxiv.org/abs/2506.13168 https://

Online-Optimized Gated Radial Basis Function Neural Network-Based Adaptive Control
Real-time adaptive control of nonlinear systems with unknown dynamics and time-varying disturbances demands precise modeling and robust parameter adaptation. While existing neural network-based strategies struggle with computational inefficiency or inadequate temporal dependencies, this study proposes a hybrid control framework integrating a Temporal-Gated Radial Basis Function (TGRBF) network with a nonlinear robust controller. The TGRBF synergizes radial basis function neural networks (RBFNNs…

Sensor Model Identification via Simultaneous Model Selection and State Variable Determination
Christian Brommer, Alessandro Fornasier, Jan Steinbrener, Stephan Weiss
https://arxiv.org/abs/2506.11263

Sensor Model Identification via Simultaneous Model Selection and State Variable Determination
We present a method for the unattended gray-box identification of sensor models commonly used by localization algorithms in the field of robotics. The objective is to determine the most likely sensor model for a time series of unknown measurement data, given an extendable catalog of predefined sensor models. Sensor model definitions may require states for rigid-body calibrations and dedicated reference frames to replicate a measurement based on the robot's localization state. A health metric is…

Joint Angle and Velocity-Estimation for Target Localization in Bistatic mmWave MIMO Radar in the Presence of Clutter
Priyanka Maity, Suraj Srivastava, Aditya K. Jagannatham, Lajos Hanzo
https://arxiv.org/abs/2506.11497

Joint Angle and Velocity-Estimation for Target Localization in Bistatic mmWave MIMO Radar in the Presence of Clutter
Sparse Bayesian learning (SBL)-aided target localization is conceived for a bistatic mmWave MIMO radar system in the presence of unknown clutter, followed by the development of an angle-Doppler (AD)-domain representation of the target-plus-clutter echo model for accurate target parameter estimation. The proposed algorithm exploits the three-dimensional (3D) sparsity arising in the AD domain of the scattering scene and employs the powerful SBL framework for the estimation of target parameters, s…

Fundamental Limits of Learning High-dimensional Simplices in Noisy Regimes
Seyed Amir Hossein Saberi, Amir Najafi, Abolfazl Motahari, Babak H. khalaj
https://arxiv.org/abs/2506.10101

Fundamental Limits of Learning High-dimensional Simplices in Noisy Regimes
In this paper, we establish sample complexity bounds for learning high-dimensional simplices in $\mathbb{R}^K$ from noisy data. Specifically, we consider $n$ i.i.d. samples uniformly drawn from an unknown simplex in $\mathbb{R}^K$, each corrupted by additive Gaussian noise of unknown variance. We prove an algorithm exists that, with high probability, outputs a simplex within $\ell_2$ or total variation (TV) distance at most $\varepsilon$ from the true simplex, provided $n \ge (K^2/\varepsilon^2…

Data-driven approaches to inverse problems
Carola-Bibiane Sch\"onlieb, Zakhar Shumaylov
https://arxiv.org/abs/2506.11732 https://

Data-driven approaches to inverse problems
Inverse problems are concerned with the reconstruction of unknown physical quantities using indirect measurements and are fundamental across diverse fields such as medical imaging, remote sensing, and material sciences. These problems serve as critical tools for visualizing internal structures beyond what is visible to the naked eye, enabling quantification, diagnosis, prediction, and discovery. However, most inverse problems are ill-posed, necessitating robust mathematical treatment to yield m…

Set-valued regression and cautious suboptimization: From noisy data to optimality
Jaap Eising, Jorge Cortes
https://arxiv.org/abs/2506.07622 https://

Set-valued regression and cautious suboptimization: From noisy data to optimality
This paper deals with the problem of finding suboptimal values of an unknown function on the basis of measured data corrupted by bounded noise. As a prior, we assume that the unknown function is parameterized in terms of a number of basis functions. Inspired by the informativity approach, we view the problem as the suboptimization of the worst-case estimate of the function. The paper provides closed form solutions and convexity results for this function, which enables us to solve the problem. A…

Accessible Design in Integrated Development Environments: A Think Aloud Study Exploring the Experiences of Students with ADHD
Luke Halpin, Phillip Benachour, Tracy Hall, Ann-Marie Houghton, Emily Winter
https://arxiv.org/abs/2506.10598

Accessible Design in Integrated Development Environments: A Think Aloud Study Exploring the Experiences of Students with ADHD
Coding forms a key part of computer science education in universities. As part of this education, Integrated Development Environments (IDEs) are essential tools for coding. However, it is currently unknown how the design of an IDE's interface impacts on students with Attention Deficit Hyperactivity Disorder (ADHD). In this study we investigated the use of IDEs by students with ADHD. We conducted a think aloud study with nine university computing students, followed by qualitative observational…

wordnet: WordNet relationships
A network of English words from the WordNet. Node is a word, and edge denotes relationships between words (synonymy, hyperonymy, meronymy, etc.). The date at which this network was extracted from WordNet is not unknown.
This network has 146005 nodes and 656999 edges.
Tags: Informational, Language, Unweighted
htt…

Effect Decomposition of Functional-Output Computer Experiments via Orthogonal Additive Gaussian Processes
Yu Tan, Yongxiang Li, Xiaowu Dai, Kwok-Leung Tsui
https://arxiv.org/abs/2506.12701

Effect Decomposition of Functional-Output Computer Experiments via Orthogonal Additive Gaussian Processes
Functional ANOVA (FANOVA) is a widely used variance-based sensitivity analysis tool. However, studies on functional-output FANOVA remain relatively scarce, especially for black-box computer experiments, which often involve complex and nonlinear functional-output relationships with unknown data distribution. Conventional approaches often rely on predefined basis functions or parametric structures that lack the flexibility to capture complex nonlinear relationships. Additionally, strong assumptio…

Probing Non-Thermal Processes in Stellar Flares on AU Mic
Adalyn Gibson, Adam F. Kowalski, Adina D. Feinstein
https://arxiv.org/abs/2506.10201 https://

Probing Non-Thermal Processes in Stellar Flares on AU Mic
The role of non-thermal proton energy transportation during solar and stellar flares is largely unknown; a better understanding of this physical process will allow us to rectify longstanding deficiencies in flare models. One way to detect the presence of non-thermal protons during flares is through the Orrall-Zirker (OZ) effect whereby an enhanced red wing appears in hydrogen emission lines (e.g., Lyman-$α$ at 1215.67 Angstrom). We analyze archival Hubble Space Telescope/Cosmic Origins Spectro…

DEKC: Data-Enable Control for Tethered Space Robot Deployment in the Presence of Uncertainty via Koopman Operator Theory
Ao Jin, Qinyi Wang, Sijie Wen, Ya Liu, Ganghui Shen, Panfeng Huang, Fan Zhang
https://arxiv.org/abs/2506.08319

DEKC: Data-Enable Control for Tethered Space Robot Deployment in the Presence of Uncertainty via Koopman Operator Theory
This work focuses the deployment of tethered space robot in the presence of unknown uncertainty. A data-enable framework called DEKC which contains offline training part and online execution part is proposed to deploy tethered space robot in the presence of uncertainty. The main idea of this work is modeling the unknown uncertainty as a dynamical system, which enables high accuracy and convergence of capturing uncertainty. The core part of proposed framework is a proxy model of uncertainty, whi…

Experimental Design for Semiparametric Bandits
Seok-Jin Kim, Gi-Soo Kim, Min-hwan Oh
https://arxiv.org/abs/2506.13390 https://arxiv.o…

Experimental Design for Semiparametric Bandits
We study finite-armed semiparametric bandits, where each arm's reward combines a linear component with an unknown, potentially adversarial shift. This model strictly generalizes classical linear bandits and reflects complexities common in practice. We propose the first experimental-design approach that simultaneously offers a sharp regret bound, a PAC bound, and a best-arm identification guarantee. Our method attains the minimax regret $\tilde{O}(\sqrt{dT})$, matching the known lower bound for …

Certifying asymmetry in the configuration of three qubits
Abdelmalek Taoutioui, G\'abor Dr\'otos, Tam\'as V\'ertesi
https://arxiv.org/abs/2506.09939

Certifying asymmetry in the configuration of three qubits
We certify asymmetry in the configuration of the Bloch vectors of a set of three unknown qubit states within the dimensionally bounded prepare-and-measure scenario. To do this, we construct a linear witness from three simpler witnesses as building blocks, each featuring, along with two binary measurement settings, three preparations; two of them are associated with the certification task, while the third one serves as an auxiliary. The final witness is chosen to self-test some target configurat…

Bayesian inference for the learning rate in Generalised Bayesian inference
Jeong Eun Lee, Sitong Liu, Geoff K. Nicholls
https://arxiv.org/abs/2506.12532 ht…

Bayesian inference for the learning rate in Generalised Bayesian inference
In Generalised Bayesian Inference (GBI), the learning rate and hyperparameters of the loss must be estimated. However, these inference-hyperparameters can't be estimated jointly with the other parameters by giving them a prior, as we discuss. Several methods for estimating the learning rate have been given which elicit and minimise a loss based on the goals of the overall inference (in our case, prediction of new data). However, in some settings there exists an unknown ``true'' learning rate ab…

ambassador: Philippines Ambassador bombing (2000)
A temporal network representing snapshots of relationships among individuals directly or indirectly associated with Philippines Ambassador Residence Bombing 2000, Jakarta. Nodes are people, and an edge exists if they are associated with each other. Definition of the edge weight is unknown.
This network has 16 nodes and 69 edges.
Tags: Social, Offline, Weighted, Temporal

The Invariant Zonotopic Set-Membership Filter for State Estimation on Groups
Tao Li, Yi Li, Lulin Zhang, Jiuxiang Dong
https://arxiv.org/abs/2506.08530 htt…

The Invariant Zonotopic Set-Membership Filter for State Estimation on Groups
The invariant filtering theory based on the group theory has been successful in statistical filtering methods. However, there exists a class of state estimation problems with unknown statistical properties of noise disturbances, and it is worth discussing whether the invariant observer still has performance advantages. In this paper, considering the problem of state estimation with unknown but bounded noise disturbances, an Invariant Zonotopic Set-Membership Filter (InZSMF) method on groups is …

Improved Uncooperative Spacecraft Maneuver Detection with Space-based Optical Observations
Xuejian Mao, Pei Liu, Pei Chen
https://arxiv.org/abs/2506.11435 …

Improved Uncooperative Spacecraft Maneuver Detection with Space-based Optical Observations
Building and maintaining a space object catalog is necessary for space situational awareness. To realize this, one great challenge is uncooperative spacecraft maneuver detection because unknown maneuver events can lead to deviated orbital predictions and losses of tracking. Nowadays, more and more spacecraft equip electric propulsion and perform long-duration maneuvers to realize orbital transfer. Previous studies have investigated impulsive maneuver detection with space surveillance data. But,…

This https://arxiv.org/abs/2412.07664 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Dynamic Obstacle Avoidance of Unmanned Surface Vehicles in Maritime Environments Using Gaussian Processes Based Motion Planning
During recent years, unmanned surface vehicles are extensively utilised in a variety of maritime applications such as the exploration of unknown areas, autonomous transportation, offshore patrol and others. In such maritime applications, unmanned surface vehicles executing relevant missions that might collide with potential static obstacles such as islands and reefs and dynamic obstacles such as other moving unmanned surface vehicles. To successfully accomplish these missions, motion planning a…

Time-domain field correlation measurements enable tomography of highly multimode quantum states of light
Emanuel Hubenschmid, Guido Burkard
https://arxiv.org/abs/2506.10483

Time-domain field correlation measurements enable tomography of highly multimode quantum states of light
Recent progress in ultrafast optics facilitates the investigation of the dynamics of highly multimode quantum states of light, as demonstrated by the application of electro-optic sampling to quantum states of the electromagnetic field. Yet, the complete tomographic reconstruction of optical quantum states with prior unknown statistics and dynamics is still challenging, since state-of-the-art tomographic methods require the measurement of many orthogonal, distinguishable modes. Here, we propose …

NASA’s Goddard Institute for Space Studies (GISS)
has been a small-but-mighty source of world-changing scientific research for more than a half-century.
NASA scientists first moved into the building,
which another federal agency leases from GISS’s institutional partner, Columbia University, in 1966.
Last month, at the behest of the Trump administration,
NASA officials told GISS it had to move out before the end of May.
In response, more than 100 staffer…

NASA’s Goddard Institute for Space Studies Faces Eviction under Trump Plan
Since 1966 NASA’s Goddard Institute for Space Studies has been at the forefront of Earth and planetary science from its location in upper Manhattan. Now a Trump administration directive is ejecting its scientists to parts unknown

ambassador: Philippines Ambassador bombing (2000)
A temporal network representing snapshots of relationships among individuals directly or indirectly associated with Philippines Ambassador Residence Bombing 2000, Jakarta. Nodes are people, and an edge exists if they are associated with each other. Definition of the edge weight is unknown.
This network has 16 nodes and 69 edges.
Tags: Social, Offline, Weighted, Temporal

This https://arxiv.org/abs/2502.20636 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Delayed-Decision Motion Planning in the Presence of Multiple Predictions
Reliable automated driving technology is challenged by various sources of uncertainties, in particular, behavioral uncertainties of traffic agents. It is common for traffic agents to have intentions that are unknown to others, leaving an automated driving car to reason over multiple possible behaviors. This paper formalizes a behavior planning scheme in the presence of multiple possible futures with corresponding probabilities. We present a maximum entropy formulation and show how, under certai…

Quantum mixture-density network for multimodal probabilistic prediction
Jaemin Seo
https://arxiv.org/abs/2506.09497 https://arxiv.org…

Quantum mixture-density network for multimodal probabilistic prediction
Multimodal probability distributions are common in both quantum and classical systems, yet modeling them remains challenging when the number of modes is large or unknown. Classical methods such as mixture-density networks (MDNs) scale poorly, requiring parameter counts that grow quadratically with the number of modes. We introduce a Quantum Mixture-Density Network (Q-MDN) that employs parameterized quantum circuits to efficiently model multimodal distributions. By representing an exponential nu…

This https://arxiv.org/abs/2308.08478 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Episodic Bayesian Optimal Control with Unknown Randomness Distributions
Stochastic optimal control with unknown randomness distributions has been studied for a long time, encompassing robust control, distributionally robust control, and adaptive control. We propose a new episodic Bayesian approach that incorporates Bayesian learning with optimal control. In each episode, the approach learns the randomness distribution with a Bayesian posterior and subsequently solves the corresponding Bayesian average estimate of the true problem. The resulting policy is exercised …

Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds
Vahan Arsenyan, Elen Vardanyan, Arnak Dalalyan
https://arxiv.org/abs/2506.09681

Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds
Generative modeling aims to produce new random examples from an unknown target distribution, given access to a finite collection of examples. Among the leading approaches, denoising diffusion probabilistic models (DDPMs) construct such examples by mapping a Brownian motion via a diffusion process driven by an estimated score function. In this work, we first provide empirical evidence that DDPMs are robust to constant-variance noise in the score evaluations. We then establish finite-sample guara…

chicago_road: Chicago road network
A transportation network of Chicago, USA, from an unknown date (probably late 20th century). Nodes represent intersections or endpoints and edge represent the road connecting these nodes.
This network has 12982 nodes and 39018 edges.
Tags: Transportation, Roads, Unweighted
https://

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning
Octavio Arriaga, Rebecca Adam, Melvin Laux, Lisa Gutzeit, Marco Ragni, Jan Peters, Frank Kirchner
https://arxiv.org/abs/2506.08756

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning
Real-world robotic applications, from autonomous exploration to assistive technologies, require adaptive, interpretable, and data-efficient learning paradigms. While deep learning architectures and foundation models have driven significant advances in diverse robotic applications, they remain limited in their ability to operate efficiently and reliably in unknown and dynamic environments. In this position paper, we critically assess these limitations and introduce a conceptual framework for com…

Constrained Pareto Set Identification with Bandit Feedback
Cyrille Kone, Emilie Kaufmann, Laura Richert
https://arxiv.org/abs/2506.08127 https://

Constrained Pareto Set Identification with Bandit Feedback
In this paper, we address the problem of identifying the Pareto Set under feasibility constraints in a multivariate bandit setting. Specifically, given a $K$-armed bandit with unknown means $μ_1, \dots, μ_K \in \mathbb{R}^d$, the goal is to identify the set of arms whose mean is not uniformly worse than that of another arm (i.e., not smaller for all objectives), while satisfying some known set of linear constraints, expressing, for example, some minimal performance on each objective. Our focu…

ambassador: Philippines Ambassador bombing (2000)
A temporal network representing snapshots of relationships among individuals directly or indirectly associated with Philippines Ambassador Residence Bombing 2000, Jakarta. Nodes are people, and an edge exists if they are associated with each other. Definition of the edge weight is unknown.
This network has 16 nodes and 4 edges.
Tags: Social, Offline, Weighted, Temporal

chicago_road: Chicago road network
A transportation network of Chicago, USA, from an unknown date (probably late 20th century). Nodes represent intersections or endpoints and edge represent the road connecting these nodes.
This network has 12982 nodes and 39018 edges.
Tags: Transportation, Roads, Unweighted
https://

ambassador: Philippines Ambassador bombing (2000)
A temporal network representing snapshots of relationships among individuals directly or indirectly associated with Philippines Ambassador Residence Bombing 2000, Jakarta. Nodes are people, and an edge exists if they are associated with each other. Definition of the edge weight is unknown.
This network has 16 nodes and 13 edges.
Tags: Social, Offline, Weighted, Temporal