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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 1131–1140 of 2226 papers

TitleStatusHype
Procedure Planning in Instructional Videos via Contextual Modeling and Model-based Policy Learning—0
Programs as Singularities—0
Projecting basis functions with tensor networks for Gaussian process regression—0
Provable Bayesian Inference via Particle Mirror Descent—0
Pruning a neural network using Bayesian inference—0
Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models—0
Pseudo-Marginal Bayesian Inference for Gaussian Processes—0
Pseudo-Marginal Hamiltonian Monte Carlo—0
Quantification of Ebola virus replication kinetics in vitro—0
Quantifying active and resistive stresses in adherent cells—0
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Benchmark Results

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