stein discrepancy

SteinGate: Tail-Sensitive Safe Reinforcement Learning via Stein Discrepancy UAI 2026 The Polynomial Stein Discrepancy for Assessing Moment Convergence ICML 2025 Information-Directed Pessimism for Offline Reinforcement Learning ICML 2024 Measuring Sample Quality in Algorithms for Intractable Normalizing Function Problems JMLR 2024 A Kernelized Stein Discrepancy for Biological Sequences ICML 2023 Bayesian Data Selection JMLR 2023 Fast and scalable score-based kernel calibration tests UAI 2023 Gradient-Free Kernel Stein Discrepancy NeurIPS 2023 STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning ICML 2023 Stein Π-Importance Sampling NeurIPS 2023 A Kernelised Stein Statistic for Assessing Implicit Generative Models NeurIPS 2022 A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family JMLR 2021 A Stein Goodness-of-test for Exponential Random Graph Models AISTATS 2021 Bridging Explicit and Implicit Deep Generative Models via Neural Stein Estimators NeurIPS 2021 Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold ICML 2021 On Energy-Based Models with Overparametrized Shallow Neural Networks ICML 2021 Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models ICML 2021 A Stein Goodness-of-fit Test for Directional Distributions AISTATS 2020 Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling ICML 2020 Stochastic Stein Discrepancies NeurIPS 2020 A Stein–Papangelou Goodness-of-Fit Test for Point Processes AISTATS 2019 Kernel Stein Tests for Multiple Model Comparison NeurIPS 2019 Minimum Stein Discrepancy Estimators NeurIPS 2019 Stein Point Markov Chain Monte Carlo ICML 2019 Goodness-of-Fit Testing for Discrete Distributions via Stein Discrepancy ICML 2018