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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 2041–2050 of 2226 papers

TitleStatusHype
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
Approximate Inference with the Variational Holder Bound—0
Sampling constrained probability distributions using Spherical Augmentation—0
Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma AugmentationCode0
Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random BasesCode0
Learning Deep Generative Models with Doubly Stochastic MCMC—0
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Benchmark Results

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