Stochastic Processes

Score-Based Generative Modeling with Critically-Damped Langevin Diffusion ICLR 2022 Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems ICML 2022 Seizing Critical Learning Periods in Federated Learning AAAI 2022 SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning UAI 2022 Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations AAAI 2022 Shuffle Private Linear Contextual Bandits ICML 2022 SIXO: Smoothing Inference with Twisted Objectives NeurIPS 2022 Social Learning in Non-Stationary Environments ALT 2022 Spatial Multivariate Trees for Big Data Bayesian Regression JMLR 2022 Spectral Representation of Robustness Measures for Optimization Under Input Uncertainty ICML 2022 Speech Enhancement with Score-Based Generative Models in the Complex STFT Domain Interspeech 2022 Stability and Generalization for Markov Chain Stochastic Gradient Methods NeurIPS 2022 Stability Based Generalization Bounds for Exponential Family Langevin Dynamics ICML 2022 State Dependent Performative Prediction with Stochastic Approximation AISTATS 2022 State Deviation Correction for Offline Reinforcement Learning AAAI 2022 Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert ICML 2022 Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning ICML 2022 Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion CVPR 2022 Stochastic Zeroth-Order Optimization under Nonstationarity and Nonconvexity JMLR 2022 Strength of Minibatch Noise in SGD ICLR 2022 Structured Stochastic Gradient MCMC ICML 2022 Structure-Preserving Learning Using Gaussian Processes and Variational Integrators L4DC 2022 Structuring Uncertainty for Fine-Grained Sampling in Stochastic Segmentation Networks NeurIPS 2022 Surprising Instabilities in Training Deep Networks and a Theoretical Analysis NeurIPS 2022 Surrogate Likelihoods for Variational Annealed Importance Sampling ICML 2022