Probability & Statistics · Mathematics & Statistics
Probability
The newest papers in Probability that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
298 papers, from 31 August 2026 to 5 November 2026: 270 arXiv preprints and 28 OpenAlex records.
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Newest papers, page 12
Predictive Uncertainty for Neural CAE Surrogates
Neural surrogates can substantially accelerate computer-aided engineering (CAE) workflows, but their use in design requires uncertainty estimates that remain meaningful across varying geometries…Risk diversification for infinitely divisible distributions
In this paper, we study the diversification properties of convex combinations of iid random variables with infinitely divisible distributions.A Kernel Approach to Multivariate Generalized Gammas Convolutions
We propose a kernel-based estimation framework for Multivariate Generalized Gamma convolutions (MGGC), a class of probability distributions on R d + .Contributions to the hierarchy of probabilistic languages
We reconsider the theory of probabilistic formal languages generated by n-gram models and by probabilistic context-free grammars (PCFGs).Risk Measures under Paired-Ambiguity: A Deep Learning Reflected BSDE Framework
We study optimal stopping under dynamic risk measures with simultaneous ambiguity in the probability model and the discount rate.Iterative Atom Refinement: A Monotonicity Principle for Dictionary Learning
Dictionary learning seeks to recover an unknown dictionary $A$ from observations ${\bf y}_i = A{\bf x}_i$ with sparse coefficient vectors ${\bf x}_i$.The Probabilistic Structure of Large Language Models
This paper presents a probabilistic perspective on large language models (LLMs), developed with the aim of bringing together, in a single self-contained account, tools that are usually treated…Toscani-Fourier Distance on Probability Measures: Wasserstein Control, Topological Equivalence on Model Classes, and Duality
Comparing probability measures in machine learning trades transport geometry against computational cost: Wasserstein distances encode the geometry of $\mathbb R^d$ but require solving a transport…The Price of Self-Calibration: Exact Evidence Budgets and Manufactured Blind Sets in Adaptive Monitoring
Self-calibrating monitors adapt their threshold online to guarantee a prescribed long-run false-alarm rate under arbitrary drift.Equilibrium prices under hidden Markov fundamentals
We study a representative-agent Epstein-Zin economy with geometric dividends and a hidden finite-state Markov drift.Quadratic and $p$-th variation of random signed Takagi--Landsberg bridges
We study random signed Takagi--Landsberg bridges with independent Rademacher Faber--Schauder coefficients.Spectral Gap of Down-Up Walks via Trickle-Down: A Simplified and Sharpened Analysis
Local-to-global techniques for establishing spectral gaps have played a central role in the modern theory of Markov chain mixing times and the theory of high-dimensional expanders.Next-token functional estimation
Suppose we observe the first $n$ points of a sequence of random variables having length $n+1$, and wish to estimate a functional of the unobserved final point and the empirical measure of the $n$…Improved Algorithms for Beck--Fiala with Bounded Sets
We give an efficient algorithm with improved algorithmic guarantees for the (offline) Beck--Fiala problem when the sets have bounded size.Sharp spectral norm concentration of sparse random tensors
We prove a sharp concentration inequality for the spectral norm of sparse random tensors with independent Bernoulli entries.Fast FPRAS for the Permanent
We give an FPRAS for the permanent of an $n\times n$ $0/1$ matrix with running time $\widetilde{O}(n^{3.5}\varepsilon^{-2})$.Efficient computation of mixture confidence sequences in generalized linear models
Classical confidence intervals, when repeatedly obtained on accumulating data at different sample sizes, produce contradictory inferences with high probability.A quantitative tree-likeness bound from average hyperbolicity
Chatterjee and Sloman proved that a bounded measurable similarity function with sufficiently small average Gromov hyperbolicity admits a tree representation with small mean approximation error.Preservation of Log-Concavity and Convergence of Wasserstein-Fisher-Rao Gradient Flows
We study the convergence of Wasserstein-Fisher-Rao (WFR) gradient flows for sampling from probability distributions known up to a normalisation constant.Total Variation Distance Estimation through Domain Reduction
Computing the total variation (TV) distance between succinctly represented high-dimensional distributions is generally intractable.