Bayesian & Probabilistic

Stochastic Generative Flow Networks UAI 2023 Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels ICML 2023 Structure Learning with Adaptive Random Neighborhood Informed MCMC NeurIPS 2023 Taming Continuous Posteriors for Latent Variational Dialogue Policies AAAI 2023 Tensor Gaussian Process with Contraction for Multi-Channel Imaging Analysis ICML 2023 The Bayesian Learning Rule JMLR 2023 The d-Separation Criterion in Categorical Probability JMLR 2023 The Fine Print on Tempered Posteriors ACML 2023 The Lauritzen-Chen Likelihood For Graphical Models AISTATS 2023 Tight Bounds on the Hardness of Learning Simple Nonparametric Mixtures COLT 2023 Tighter PAC-Bayes Bounds Through Coin-Betting COLT 2023 TopicFM: Robust and Interpretable Topic-Assisted Feature Matching AAAI 2023 Towards a Complete Analysis of Langevin Monte Carlo: Beyond Poincaré Inequality COLT 2023 Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes ICML 2023 Tractable and Near-Optimal Adversarial Algorithms for Robust Estimation in Contaminated Gaussian Models JMLR 2023 Training Energy-Based Normalizing Flow with Score-Matching Objectives NeurIPS 2023 Transfer NAS with Meta-learned Bayesian Surrogates ICLR 2023 Transformed Gaussian Processes for Characterizing a Model’s Discrepancy ACML 2023 Transport Elliptical Slice Sampling AISTATS 2023 Trusted Fine-Grained Image Classification through Hierarchical Evidence Fusion AAAI 2023 Unbiased constrained sampling with Self-Concordant Barrier Hamiltonian Monte Carlo NeurIPS 2023 Unbiased Multilevel Monte Carlo Methods for Intractable Distributions: MLMC Meets MCMC JMLR 2023 Uncertainty Estimation for Molecules: Desiderata and Methods ICML 2023 Undirected Probabilistic Model for Tensor Decomposition NeurIPS 2023 Uniqueness of BP fixed point for the Potts model and applications to community detection COLT 2023