Probability & Statistics · Mathematics & Statistics
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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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Learning Finite-Memory Binary Sources
Estimating biased finite-memory sources from a single trajectory is a fundamental problem with practical impact, for example in estimating entropy for cryptography.Analysis of Triggered Packet Streams: Stochastic Bounds on System Time under General Triggering Delays
Many emerging communication systems increasingly involve devices that transmit packets in multiple causally dependent stages as part of an internal workflow, rather than waiting for receiver feedback.When can Optimally Trained Transformers Achieve Near-Lossless Token Prediction for non-Markovian Data?
There exists little mathematical theory explaining why Transformer architectures are empirically successful even for non-Markovian data.Computer-Assisted Results for \(n\)-Sided Non-Transitive Dice Taking Face Values in \([n]\)
We consider non-transitivity among dice with \(n\) sides restricted to taking face values in the set \(\{1,\ldots,n\}\).Averaged Annealed Markov Chains Achieve the Algorithmic Threshold for Tensor PCA, Part II: Langevin Dynamics
We consider the tensor principal components analysis (tensor PCA) problem on the sphere, in which we are asked to recover an unknown vector in $\mathcal{S}_N=\{x\in\mathbb{R}^N:\lVert x\rVert^2=N\}$…Capacity of the Hopfield-Hebbian dynamics with correlated patterns
Allowing for small fraction of errors in retrieved stored binary patterns, Hopfield-Hebbian neural network (NN) associative memory dynamics [14] achieves linearly scaled capacity.Calibration of Passive Market Impact with a Queue-Sensitive Propagator Model
We develop a framework for calibrating passive market impact, defined as the price response to liquidity-providing limit orders, in contrast to the impact of liquidity-consuming market orders.Metropolized backward sampling for conditional sequential Monte Carlo
Particle Gibbs samplers with backward sampling are widely used for sampling the smoothing distribution of state-space models, but, with few particles, the new trajectory often coincides with the…Underdamped Anchored Langevin Dynamics
Classical Langevin Monte Carlo algorithms, such as the unadjusted Langevin algorithm (ULA), are based on discretization schemes of the overdamped Langevin dynamics and are widely used for sampling…Risk measures for infinite-server queues driven by a Cox-BESQ process
This paper introduces a model for infinite-server queues driven by a Cox process with stochastic intensity given by a squared Bessel (BESQ) process.Holomorphic Cauchy Networks for Efficient Stationary Tail Computation in High-Dimensional Reflected Brownian Motions
Stationary tail computation for high-dimensional reflected Brownian motions (RBMs) remains computationally challenging.RePAIR: Inverting Backdoor Attacks in Semantic Segmentation
Despite significant advances in computer vision, semantic segmentation models remain vulnerable to backdoor attacks, posing a security risk.Para-Gaussian Approximations of Random Deep Neural Networks
It is known that randomly initialized neural networks have Gaussian behaviour in the $n\to \infty$ limit.Displacement Moments and Path-Terminal Separation in Brownian Interpolant Sampling
Brownian stochastic interpolants connect paired endpoint samples, yet their sampling error can depend on displacement moments even when neither endpoint has a first moment.Approximate Counting for Mixed $p$-Spin Glasses in Weak External Fields via Cluster Expansion
We give algorithms for approximating the partition function $Z_N$ of the Sherrington--Kirkpatrick (SK) model and finite mixed Ising $p$-spin models with $p\ge 3$.Local-to-Global Theorems Based on Cones with Applications to Graph Coloring
Local-to-Global theorems are a cornerstone of many of recent developments in theoretical computer science from coding theory and PCPs all the way to analyzing mixing time of Markov chains.Finite-Sample Optimal Conformal Prediction Sets under Covariate Shift
We study conformal prediction under covariate shift with a known covariate density ratio, seeking prediction sets with minimum expected length under the target distribution.Spectral delocalization and central limit theorems for Fourier functionals of stationary Gaussian fields
We characterize Gaussian fluctuations of Fourier-Hermite functionals of stationary Gaussian fields on locally compact Abelian groups via spectral delocalization: conditional on the total spectral…Beyond Multiplicity Correction: Sharp Retrieval Thresholds for Attention with Correlated Distractors
Redundant context affects attention in two distinct ways: multiplicity adds normalization mass, while score variation within correlated groups can produce extreme individual scores.Linear Hashing Is Poissonesque
The Poisson approximation theorem states that when $m$ balls are tossed uniformly and randomly into $n$ bins, the distribution of the bin loads can sometimes be approximated by $n$ independent…