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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 561–570 of 2226 papers

TitleStatusHype
Amortized Bayesian Inference for Models of Cognition—0
Building fast Bayesian computing machines out of intentionally stochastic, digital parts—0
A Variational View on Bootstrap Ensembles as Bayesian Inference—0
A Variational Observation Model of 3D Object for Probabilistic Semantic SLAM—0
Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation—0
A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM—0
A Variational Bayesian Inference Theory of Elasticity and Its Mixed Probabilistic Finite Element Method for Inverse Deformation Solutions in Any Dimension—0
Variational inference of fractional Brownian motion with linear computational complexity—0
ABC random forests for Bayesian parameter inference—0
Building general Langevin models from discrete data sets—0
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Benchmark Results

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