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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 1971–1980 of 2226 papers

TitleStatusHype
Coresets for Scalable Bayesian Logistic RegressionCode0
ABC random forests for Bayesian parameter inference—0
An Efficient and Flexible Spike Train Model via Empirical Bayes—0
High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm—0
Fast Rates for General Unbounded Loss Functions: from ERM to Generalized Bayes—0
Bayesian Inference of Recursive Sequences of Group Activities from Tracks—0
Variational Bayesian Inference of Line Spectra—0
A Formal Calculus for International Relations Computation and Evaluation—0
Bayesian inference in hierarchical models by combining independent posteriors—0
GPU Computing in Bayesian Inference of Realized Stochastic Volatility Model—0
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Benchmark Results

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