Stochastic Processes

USHER: Unbiased Sampling for Hindsight Experience Replay CoRL 2022 Variational Marginal Particle Filters AISTATS 2022 Variational multiple shooting for Bayesian ODEs with Gaussian processes UAI 2022 Variational Neural Cellular Automata ICLR 2022 Wavelet Score-Based Generative Modeling NeurIPS 2022 WeaNF”:" Weak Supervision with Normalizing Flows ACL 2022 When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits NeurIPS 2022 Why the Rich Get Richer? On the Balancedness of Random Partition Models ICML 2022 Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling ICML 2022 A Biased Graph Neural Network Sampler with Near-Optimal Regret NeurIPS 2021 Adaptive Machine Unlearning NeurIPS 2021 Adjusting for Autocorrelated Errors in Neural Networks for Time Series NeurIPS 2021 Adversarial score matching and improved sampling for image generation ICLR 2021 Adversarial Spectral Kernel Matching for Unsupervised Time Series Domain Adaptation IJCAI 2021 A Generative Framework for Simultaneous Machine Translation EMNLP 2021 A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces AISTATS 2021 A Law of Iterated Logarithm for Multi-Agent Reinforcement Learning NeurIPS 2021 A Max-Min Entropy Framework for Reinforcement Learning NeurIPS 2021 An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo AISTATS 2021 Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler JMLR 2021 Analysis of one-hidden-layer neural networks via the resolvent method NeurIPS 2021 An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias NeurIPS 2021 An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling AISTATS 2021 Annealed Flow Transport Monte Carlo ICML 2021 A nonparametric method for gradual change problems with statistical guarantees NeurIPS 2021