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 211–220 of 2226 papers

TitleStatusHype
A Simple Baseline for Bayesian Uncertainty in Deep LearningCode1
ComBiNet: Compact Convolutional Bayesian Neural Network for Image SegmentationCode1
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaicsCode1
Spacecraft Collision Risk Assessment with Probabilistic ProgrammingCode1
Pick-and-Mix Information Operators for Probabilistic ODE SolversCode1
Stein Variational Gradient Descent: A General Purpose Bayesian Inference AlgorithmCode1
A Gibbs Sampler for Efficient Bayesian Inference in Sign-Identified SVARs—0
A Generative Modeling Framework for Inferring Families of Biomechanical Constitutive Laws in Data-Sparse Regimes—0
Accurate Evaluation of Asset Pricing Under Uncertainty and Ambiguity of Information—0
Accurate Direct Positioning in Distributed MIMO Using Delay-Doppler Channel Measurements—0
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Benchmark Results

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