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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 1251–1260 of 2226 papers

TitleStatusHype
Structured Dropout Variational Inference for Bayesian Neural Networks—0
ScrofaZero: Mastering Trick-taking Poker Game Gongzhu by Deep Reinforcement LearningCode0
Neural Posterior Regularization for Likelihood-Free InferenceCode0
Projected Wasserstein gradient descent for high-dimensional Bayesian inferenceCode0
Bayesian Inference with Certifiable Adversarial RobustnessCode0
Bayesian multiscale deep generative model for the solution of high-dimensional inverse problemsCode0
Bayesian Neural Networks for Virtual Flow Metering: An Empirical StudyCode0
Bayesian data-driven discovery of partial differential equations with variable coefficients—0
Modeling German Word Order Acquisition via Bayesian Inference—0
Fundamental limits and algorithms for sparse linear regression with sublinear sparsity—0
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Benchmark Results

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