Statistics Theory (math.ST)

Reversible Gromov-Monge Sampler for Simulation-Based Inference

Randomization Inference When N Equals One

High-Dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models

Detecting Weak Distribution Shifts via Displacement Interpolation

Interpolating Classifiers Make Few Mistakes

Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria

Universal Prediction Band via Semi-Definite Programming

A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-L1-Norm Interpolated Classifiers

Mehler’s Formula, Branching Process, and Compositional Kernels of Deep Neural Networks

How Well Generative Adversarial Networks Learn Distributions