Stochastic Processes

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 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 Interval-censored Hawkes processes JMLR 2022 Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence JMLR 2022 Language modeling via stochastic processes ICLR 2022 Learning and Covering Sums of Independent Random Variables with Unbounded Support NeurIPS 2022 Learning Fractional White Noises in Neural Stochastic Differential Equations NeurIPS 2022 Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences AAAI 2022 LinCDE: Conditional Density Estimation via Lindsey's Method JMLR 2022 Log-Concave and Multivariate Canonical Noise Distributions for Differential Privacy NeurIPS 2022 LSB: Local Self-Balancing MCMC in Discrete Spaces ICML 2022