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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 2031–2040 of 2226 papers

TitleStatusHype
Orthogonal parallel MCMC methods for sampling and optimization—0
String and Membrane Gaussian Processes—0
The Population Posterior and Bayesian Inference on StreamsCode1
Scalable Bayesian Inference for Excitatory Point Process NetworksCode0
Remarks on kernel Bayes' rule—0
Unifying Bayesian Inference and Vector Space Models for Improved Decipherment—0
Fast and accurate approximate inference of transcript expression from RNA-seq dataCode0
Scalable Discrete Sampling as a Multi-Armed Bandit Problem—0
Factorized Asymptotic Bayesian Inference for Factorial Hidden Markov Models—0
Sampling constrained probability distributions using Spherical Augmentation—0
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Benchmark Results

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