approximate bayesian inference

Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC JMLR 2024 Model-based Policy Optimization under Approximate Bayesian Inference AISTATS 2024 A Bayesian approach to breaking things: efficiently predicting and repairing failure modes via sampling CoRL 2023 Bounded rationality in structured density estimation NeurIPS 2023 Fast Expectation Propagation for Heteroscedastic, Lasso-Penalized, and Quantile Regression JMLR 2023 Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference AISTATS 2022 Surrogate Likelihoods for Variational Annealed Importance Sampling ICML 2022 De-randomizing MCMC dynamics with the diffusion Stein operator NeurIPS 2021 Out-of-Distribution Detection Using Union of 1-Dimensional Subspaces CVPR 2021 Sparse Algorithms for Markovian Gaussian Processes AISTATS 2021 Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse NeurIPS 2019 Approximate Bayesian Inference in Spatial Environments RSS 2019 Calibrated Approximate Bayesian Inference ICML 2019 Random Feature Stein Discrepancies NeurIPS 2018 Stochastic Expectation Propagation NeurIPS 2015 Semi-supervised Learning with Deep Generative Models NeurIPS 2014 Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs NeurIPS 2013 Bayesian Experimental Design of Magnetic Resonance Imaging Sequences NeurIPS 2008 An Approximate Analytical Approach to Resampling Averages JMLR 2003