SOTAVerified

Bayesian Inference

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

Papers

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Showing 1111–1120 of 2226 papers

TitleStatusHype
On out-of-distribution detection with Bayesian neural networksCode0
Deep Bayesian inference for seismic imaging with tasksCode0
Kernel Interpolation as a Bayes Point MachineCode0
Pathologies in priors and inference for Bayesian transformers—0
De-randomizing MCMC dynamics with the diffusion Stein operator—0
MetaCOG: A Hierarchical Probabilistic Model for Learning Meta-Cognitive Visual RepresentationsCode0
Procedure Planning in Instructional Videos via Contextual Modeling and Model-based Policy Learning—0
Kalman Bayesian Neural Networks for Closed-form Online Learning—0
Arbitrary Marginal Neural Ratio Estimation for Simulation-based InferenceCode0
Semantic Classification and Learning Using a Linear Tranformation Model in a Probabilistic Type Theory with Records—0
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Benchmark Results

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