Probability Measures

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6 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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  1. Neural Harmonic Measure Operator

    Sep 28, 2026Jinjin He, Sinan Wang, Yuchen Sun +1Bayesian QuadratureProbability Measures

    Georgia Institute of Technology

  2. Universal Approximation of Measure-to-Measure Operators by Pushforwards

    Sep 28, 2026Takashi Furuya, Nicholas H. Nelsen, Frank ColeProbability MeasuresApproximation

    Doshisha University, RIKEN AIP · UT Austin · UCLA

  3. From Distributions to Stochastic Processes: Neural Approximation of Measure-Valued Maps

    Sep 27, 2026Yichen Wang, Ziyi Wang, Wenlian Lu +5Probability MeasuresStochastic Processes

    Shanghai Center for Mathematical Sciences, Shanghai, China · Department of Mathematics, Fudan University, Shanghai, China · Center for Applied Mathematics, Fudan University, Shanghai, China +2

  4. Recovering Lower-Dimensional Semialgebraic Support of a Measure from its Moments

    Sep 27, 2026Ruben Karapetyan, Shenyuan Ma, Ales Wodecki +1Probability MeasuresRiemannian Manifolds

    Czech Technical University in Prague

  5. Zero-SNR Analyticity of the Scalar MMSE Is Equivalent to Gaussianity

    Sep 14, 2026Yixing ZhangNon-GaussianityProbability Measures

  6. Deep operator learning for efficient sampling from invariant measures of stochastic differential equations

    Sep 10, 2026Ling Guo, Lei Li, Jingtong ZhangAccelerated SamplingStochastic Differential Equations

    Department of Mathematics, Shanghai Normal University, Shanghai, China · School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai, China · Institute of Natural Sciences, MOE-LSC, Shanghai Jiao Tong University, Shanghai, China

  7. A Borel Concept Class of VC Dimension One with a Non-PAC Consistent Learner in ZFC

    Aug 31, 2026Mateus Jesus de Arruda Campos, Gabriel Fernandes, Vinicius de Oliveira RodriguesProbability MeasuresAdm-Fusion

  8. Foundations of Independent Component Analysis

    Aug 13, 2026Patrick ForréIndependent Component AnalysisIdentifiability

    AI4Science Lab Korteweg-de Vries Institute for Mathematics University of Amsterdam

  9. Tropical Algebraic Geometry for Neuronal Representations: An Arakelov-Green Measure Based Descriptor for Graph Learning

    Aug 5, 2026Yuyang Zhang, Weihan Xu, Xuehai Zhou +2Graph Neural NetworksProbability Measures

    McGill University

  10. A Direct Route to Markov Chain Convergence via Asymptotic Equivalence with the Target

    Aug 4, 2026Patrick ForréMarkovProbability Measures

    AI4Science Lab Korteweg-de Vries Institute for Mathematics University of Amsterdam

  11. Operator Neural Jump ODEs: L2L^2-optimal prediction in function spaces

    Jul 25, 2026Florian Krach, Oliver Löthgren, Josef TeichmannNeural Ordinary Differential EquationsNeural Approximations

    Department of Mathematics ETH Zurich

  12. Nesterov acceleration in optimizing over probability measures

    Jul 25, 2026Jiaqi Tang, Qin Li, Wilfrid GangboMomentum Stochastic Gradient DescentProbability Measures

    Department of Statistics, University of Wisconsin–Madison, Madison, WI 53706, USA · Department of Mathematics, University of Wisconsin–Madison, Madison, WI 53706, USA · Department of Mathematics, University of California, Los Angeles, Los Angeles, CA 90095, USA

  13. On the Order-Conditional Optimality of Gaffke's Bound

    Jul 25, 2026George Bissias, Erik Learned-MillerOptimalityMaximum Likelihood

    University of Massachusetts Amherst

  14. Natural Invariant Measures for Chaotic Game Dynamics: Finding Order in Chaos

    Jul 23, 2026Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski +2ChaosProbability Measures

    Department of Mathematics, Krakow University of Economics, Rakowicka 27, 31-510 Kraków, Poland · Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University,Bangkok 10330, Thailand · Department of Mathematical Sciences, Indiana University Indianapolis,402 N. Blackford Street, Indianapolis, Indiana 46202, USA +1

  15. Kime-Representation Formulations of Three Open Problems in the Foundations of Classical Mechanics: Uncertainty, Invariant Entropy, and Directional Degrees of Freedom

    Jul 8, 2026Ivo D. DinovPhase SpaceHamiltonian

    Statistics Online Computational Resource (SOCR) University of Michigan, Ann Arbor, MI 48109, US∗

  16. Transformer Architectures as Complete Bayes Processes: A Formal Proof in the Measure-Theoretic Kernel Framework

    Jun 29, 2026Haobo YangTransformer ArchitecturesBayesian

    Department of Computer Science and Engineering, SUSTech University

  17. Value of Information under Imprecise Probabilities: Decision-Rule-Specific Values and Fixed-Measure Envelopes on a Credal Set

    Jun 26, 2026Rowan IskandarConditional-Value-At-RiskMinimax

    Medtronic Trading Sàrl, Tolochenaz, VD, Switzerland · Center for Evidence Synthesis in Health, Brown University School of Public Health, Providence, RI, USA

  18. Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence

    Jun 15, 2026Peng Xu, Changbo Zhu, Young-Heon Kim +1Wasserstein DistanceProbability Measures

    Department of Statistics University of Illinois Urbana-Champaign · Department of ACMS University of Notre Dame · Department of Mathematics University of British Columbia +1

  19. Reachability and asymptotics of Gaussian Transformer dynamics

    May 29, 2026Albert Alcalde, Zhengping Ji, Enrique ZuazuaTransformer ArchitecturesFinite Time Analysis

    †Chair for Dynamics, Control, Machine Learning & Numerics (Alexander von Humboldt Profes- sorship), Department of Mathematics, Friedrich–Alexander-Universität Erlangen–Nürnberg, 91058 Erlangen, Germany. · ‡Departamento de Matem´aticas, Universidad Aut´onoma de Madrid, 28049 Madrid, Spain. · Chair of Computational Mathematics, Fundaci´on Deusto. Av. de las Universidades, 24, 48007 Bilbao, Basque Country, Spain.

  20. On the evolution of the concept of probability as a mirror of the evolution of reason

    May 26, 2026Jean-Louis Le Mouël, Vincent Courtillot, Dominique Gibert +6Dynamic Epistemic LogicProbability

    Acad´emie des Sciences, Institut de France, Paris, France · DeepField Sensing, France · Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences, Moscow, Russia +4

  21. The Normalized Maximum Likelihood for Regular Non-Smooth Models: Measure-Theoretic Foundations and Geometric Sampling

    May 23, 2026Trenton Lau, Gary P. T. ChoiMaximum LikelihoodMarkovian Sampling

    Department of Mathematics, The Chinese University of Hong Kong, Hong Kong

  22. On the Regularity and Generalization of One-Step Wasserstein-guided Generative Models for PDE-Induced Measures

    May 20, 2026Likun Lin, Zhongjian Wang, Jack Xin +1Probability MeasuresGenerative Models

    Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, P.R. China. · Division of Mathematical Sciences, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 637371. · Department of Mathematics, University of California at Irvine, Irvine, CA 92697, USA. +1

  23. A Measure-Theoretic Analysis of Reasoning: Structural Generalization and Approximation Limits

    May 19, 2026Yuyang Zhang, Yifu Zhang, Xuehai Zhou +1Out-Of-DistributionLLM Reasoning Strategies

    McGill University · Mila - Quebec AI Institute · Université de Montréal

  24. Function graph transformers universally approximate operators between function spaces

    May 18, 2026Takashi Furuya, David Mis, Ivan Dokmanić +2Probabilistic Operator LearningMultiplex Graph Transformers

    Doshisha University, RIKEN AIP · Rice University · University of Basel +2

  25. A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models

    May 7, 2026Aditya Ranganath, Mukesh SinghalScore-Based Diffusion ModelGenerative Models

    Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore, CA 94551, USA · Department of Electrical Engineering University of California Merced, CA 95343, USA

  26. Gaussian mixture models in Hilbert spaces via kernel methods

    May 7, 2026Daniel López-Montero, Antonio Álvarez-López, Marcos MatabuenaKernel Hilbert SpacesGaussian Mixture Models

    Friedrich-Alexander-Universität Erlangen-Nürnberg · Universidad Autónoma de Madrid · Mohamed bin Zayed University of Artificial Intelligence

  27. Null Measurability at the Symmetrization Interface in VC Learning

    Apr 27, 2026Dhruv GuptaProbability MeasuresLearnability

    AI and Robotics Technology Park, Indian Institute of Science, Bengaluru

  28. The Geometry of Efficient Nonconvex Sampling

    Mar 26, 2026Santosh S. Vempala, Andre WibisonoLog-Concave DistributionsOptimal Sample Complexity

    Georgia Institute of Technology, College of Computing · Yale University, Department of Computer Science

  29. PCA of probability measures: Sparse and Dense sampling regimes

    Feb 2, 2026Gachon Erell, Jérémie Bigot, Elsa CazellesPrincipal Component AnalysisProbability Measures

    Institut de Mathématiques de Bordeaux, Université de Bordeaux, CNRS (UMR 5251) · CNRS, IRIT (UMR 5505), Université de Toulouse

  30. Structured Approximations of Measures

    Oct 13, 2023Keaton Hamm, Varun KhuranaProbability MeasuresWasserstein Distance

    DEPARTMENT OF MATHEMATICS, THE UNIVERSITY OF TEXAS AT ARLINGTON, ARLINGTON, TX · DIVISION OF DATA SCIENCE, THE UNIVERSITY OF TEXAS AT ARLINGTON, ARLINGTON, TX · DEPARTMENT OF APPLIED MATHEMATICS, BROWN UNIVERSITY, PROVIDENCE, RI 02906.