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bayesian inference

1904 papers

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Also known as

MCMC MBR BI BVMM MAP

Co-occurring keywords

variational inference (2069) markov chain monte carlo (724) gaussian process (1198) probabilistic modeling (851) uncertainty quantification (1365) posterior distribution (259) bayesian learning (185) gibbs sampling (201) graphical model (863) probabilistic model (476)

Papers

Exploiting locality in high-dimensional Factorial hidden Markov models JMLR 2022
Robust Anytime Learning of Markov Decision Processes NIPS 2022
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting JMLR 2022
Streaming Inference for Infinite Feature Models ICML 2022
Bayesian Risk Markov Decision Processes NIPS 2022
Estimating Causal Effects under Network Interference with Bayesian Generalized Propensity Scores JMLR 2022
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother JMLR 2022
Double Spike Dirichlet Priors for Structured Weighting JMLR 2022
Semi-Supervised Imitation Learning of Team Policies from Suboptimal Demonstrations IJCAI 2022
Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure JMLR 2022
Efficient Inference for Dynamic Flexible Interactions of Neural Populations JMLR 2022
On the Robustness to Misspecification of α-posteriors and Their Variational Approximations JMLR 2022
Distributed Bayesian Varying Coefficient Modeling Using a Gaussian Process Prior JMLR 2022
Bayesian Pseudo Posterior Mechanism under Asymptotic Differential Privacy JMLR 2022
Thompson Sampling with a Mixture Prior AISTATS 2022
Laplacian Autoencoders for Learning Stochastic Representations NIPS 2022
Society of Agents: Regret Bounds of Concurrent Thompson Sampling NIPS 2022
Deep Reference Priors: What is the best way to pretrain a model? ICML 2022
Infinite SCAN: An Infinite Model of Diachronic Semantic Change EMNLP 2022
A Class of Conjugate Priors for Multinomial Probit Models which Includes the Multivariate Normal One JMLR 2022
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees NIPS 2022
Meta Reinforcement Learning with Finite Training Tasks - a Density Estimation Approach NIPS 2022
A Convergence Theory for SVGD in the Population Limit under Talagrand’s Inequality T1 ICML 2022
RL with KL penalties is better viewed as Bayesian inference EMNLP 2022
Variational inference via Wasserstein gradient flows NIPS 2022