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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 501–510 of 2226 papers

TitleStatusHype
Towards a Unified Framework for Sequential Decision Making—0
Statistical physics, Bayesian inference and neural information processing—0
A Mean Field Approach to Empirical Bayes Estimation in High-dimensional Linear Regression—0
A Primer on Bayesian Neural Networks: Review and DebatesCode1
A Metaheuristic for Amortized Search in High-Dimensional Parameter SpacesCode0
Entropic Matching for Expectation Propagation of Markov Jump Processes—0
A closer look at parameter identifiability, model selection and handling of censored data with Bayesian Inference in mathematical models of tumour growth—0
BayesDLL: Bayesian Deep Learning LibraryCode1
Neural Operator Variational Inference based on Regularized Stein Discrepancy for Deep Gaussian ProcessesCode0
Bounded rationality in structured density estimation—0
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Benchmark Results

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