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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 2131–2140 of 2226 papers

TitleStatusHype
Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits—0
Locally Adaptive Bayesian Multivariate Time Series—0
Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC—0
Stochastic inference with deterministic spiking neurons—0
Exploration in Interactive Personalized Music Recommendation: A Reinforcement Learning Approach—0
Bayesian inference as iterated random functions with applications to sequential inference in graphical models—0
Variational Bayesian inference for linear and logistic regressionCode0
Improved Bayesian Logistic Supervised Topic Models with Data Augmentation—0
Discriminative Relational Topic Models—0
Pseudo-Marginal Bayesian Inference for Gaussian Processes—0
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Benchmark Results

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