SOTAVerified

Bayesian Inference

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

Papers

Showing 8190 of 2226 papers

TitleStatusHype
Bayes-Newton Methods for Approximate Bayesian Inference with PSD GuaranteesCode1
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU NetworksCode1
A Simple Baseline for Bayesian Uncertainty in Deep LearningCode1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric ApproachesCode1
Can Transformers Learn Full Bayesian Inference in Context?Code1
ComBiNet: Compact Convolutional Bayesian Neural Network for Image SegmentationCode1
Continual Learning via Sequential Function-Space Variational InferenceCode1
Convolutional Bayesian Kernel Inference for 3D Semantic MappingCode1
CosmoPower-JAX: high-dimensional Bayesian inference with differentiable cosmological emulatorsCode1
A Bayesian approach for extracting free energy profiles from cryo-electron microscopy experiments using a path collective variableCode1
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Benchmark Results

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