Probability

Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals AISTATS 2022 Adaptive Data Analysis with Correlated Observations ICML 2022 Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff AISTATS 2022 A Langevin-like Sampler for Discrete Distributions ICML 2022 Analysis of Langevin Monte Carlo from Poincare to Log-Sobolev COLT 2022 Anytime Information Cascade Popularity Prediction via Self-Exciting Processes ICML 2022 A Predictive Approach to Bayesian Nonparametric Survival Analysis AISTATS 2022 A Witness Two-Sample Test AISTATS 2022 Bounding the Error of Discretized Langevin Algorithms for Non-Strongly Log-Concave Targets JMLR 2022 Conditional Loss and Deep Euler Scheme for Time Series Generation AAAI 2022 Convergence Rates for Gaussian Mixtures of Experts JMLR 2022 Deep Neyman-Scott Processes AISTATS 2022 Density Ratio Estimation via Infinitesimal Classification AISTATS 2022 Efficiency Ordering of Stochastic Gradient Descent NeurIPS 2022 Efficient computation of the the volume of a polytope in high-dimensions using Piecewise Deterministic Markov Processes AISTATS 2022 Exact simulation of diffusion first exit times: algorithm acceleration JMLR 2022 Fenrir: Physics-Enhanced Regression for Initial Value Problems ICML 2022 FlowHMM: Flow-based continuous hidden Markov models NeurIPS 2022 Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need? NeurIPS 2022 High-dimensional limit theorems for SGD: Effective dynamics and critical scaling NeurIPS 2022 Identification, Amplification and Measurement: A bridge to Gaussian Differential Privacy NeurIPS 2022 Inference and Sampling for Archimax Copulas NeurIPS 2022 Interval-censored Hawkes processes JMLR 2022 Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence JMLR 2022 Language modeling via stochastic processes ICLR 2022