Stochastic Processes

Scalable Subset Sampling with Neural Conditional Poisson Networks ICLR 2023 Score-based Continuous-time Discrete Diffusion Models ICLR 2023 Score-based Generative Models with Lévy Processes NeurIPS 2023 Score-based Quickest Change Detection for Unnormalized Models AISTATS 2023 SE(3) Equivariant Augmented Coupling Flows NeurIPS 2023 SEEDS: Exponential SDE Solvers for Fast High-Quality Sampling from Diffusion Models NeurIPS 2023 Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains ICML 2023 Self-Supervised Blind Motion Deblurring With Deep Expectation Maximization CVPR 2023 Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing Flows ICML 2023 Sequential Monte Carlo Learning for Time Series Structure Discovery ICML 2023 Sequential Predictive Two-Sample and Independence Testing NeurIPS 2023 SGD with Large Step Sizes Learns Sparse Features ICML 2023 SGEM: Test-Time Adaptation for Automatic Speech Recognition via Sequential-Level Generalized Entropy Minimization Interspeech 2023 Sharp Variance-Dependent Bounds in Reinforcement Learning: Best of Both Worlds in Stochastic and Deterministic Environments ICML 2023 Simultaneous Learning of Contact and Continuous Dynamics CoRL 2023 Smooth Non-stationary Bandits ICML 2023 SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process ICML 2023 SONGs: Self-Organizing Neural Graphs WACV 2023 Spatio-temporal point processes with deep non-stationary kernels ICLR 2023 Spectral Decomposition Representation for Reinforcement Learning ICLR 2023 Spectral Evolution and Invariance in Linear-width Neural Networks NeurIPS 2023 Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning AAAI 2023 State and parameter learning with PARIS particle Gibbs ICML 2023 Stochastic Bridges as Effective Regularizers for Parameter-Efficient Tuning ACL 2023 Stochastic Gradient Descent under Markovian Sampling Schemes ICML 2023