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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 1691–1700 of 2226 papers

TitleStatusHype
MFRL-BI: Design of a Model-free Reinforcement Learning Process Control Scheme by Using Bayesian Inference—0
Micro-CT Synthesis and Inner Ear Super Resolution via Generative Adversarial Networks and Bayesian Inference—0
Minimum Description Length Control—0
Mixability in Statistical Learning—0
Mixture Distributions for Scalable Bayesian Inference—0
Mixture modeling on related samples by ψ-stick breaking and kernel perturbation—0
Mixture of Bilateral-Projection Two-dimensional Probabilistic Principal Component Analysis—0
Model-based Bayesian inference of neural activity and connectivity from all-optical interrogation of a neural circuit—0
Model-based Bayesian Reinforcement Learning for Dialogue Management—0
Model-based Influence Diagrams for Machine Vision—0
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Benchmark Results

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