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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1941–1950 of 2226 papers

TitleStatusHype
Fast Bayesian Inference for Neutrino Non-Standard Interactions at Dark Matter Direct Detection ExperimentsCode0
Monitoring machine learning (ML)-based risk prediction algorithms in the presence of confounding medical interventionsCode0
Bandit Learning with Implicit FeedbackCode0
Bayesian Inference with Anchored Ensembles of Neural Networks, and Application to Exploration in Reinforcement LearningCode0
Fast post-process Bayesian inference with Variational Sparse Bayesian QuadratureCode0
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical BayesCode0
Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization ProblemsCode0
MPC-guided Imitation Learning of Neural Network Policies for the Artificial PancreasCode0
Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex ModelsCode0
Reversible Jump Probabilistic ProgrammingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified