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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 831–840 of 2226 papers

TitleStatusHype
BInGo: Bayesian Intrinsic Groupwise Registration via Explicit Hierarchical Disentanglement—0
Automated Circuit Sizing with Multi-objective Optimization based on Differential Evolution and Bayesian Inference—0
Unifying Summary Statistic Selection for Approximate Bayesian ComputationCode0
Information Threshold, Bayesian Inference and Decision-Making—0
Functional Ensemble DistillationCode0
Excess risk analysis for epistemic uncertainty with application to variational inference—0
Bayesian Inference of Stochastic Dynamical Networks—0
Bayesian Inference for the Multinomial Probit Model under Gaussian Prior Distribution—0
Robust Anytime Learning of Markov Decision ProcessesCode0
Variational inference via Wasserstein gradient flowsCode1
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Benchmark Results

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