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 1331–1340 of 2226 papers

TitleStatusHype
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift—0
Multi-marginal optimal transport and probabilistic graphical modelsCode1
The principles of adaptation in organisms and machines II: Thermodynamics of the Bayesian brain—0
Constraining subglacial processes from surface velocity observations using surrogate-based Bayesian inference—0
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal PosteriorsCode0
Calibration of Model Uncertainty for Dropout Variational Inference—0
Learning to infer in recurrent biological networksCode0
Solving Differential Equations Using Neural Network Solution Bundles—0
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF—0
Hidden Markov Models Applied To Intraday Momentum Trading With Side Information—0
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Benchmark Results

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