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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 141–150 of 2226 papers

TitleStatusHype
Dangers of Bayesian Model Averaging under Covariate ShiftCode1
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reductionCode1
A practical tutorial on Variational BayesCode1
BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy imagesCode1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric ApproachesCode1
Diffusive Gibbs SamplingCode1
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context LearningCode1
A Primer on Bayesian Neural Networks: Review and DebatesCode1
A Probabilistic State Space Model for Joint Inference from Differential Equations and DataCode1
Bayes-Newton Methods for Approximate Bayesian Inference with PSD GuaranteesCode1
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Benchmark Results

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