SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 361–370 of 2226 papers

TitleStatusHype
Variational Bayesian surrogate modelling with application to robust design optimisation—0
Scalable Data Assimilation with Message PassingCode0
Underdetermined DOA Estimation of Off-Grid Sources Based on the Generalized Double Pareto Prior—0
BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models—0
Neural Methods for Amortized Inference—0
Aligning language models with human preferencesCode2
Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference—0
Analytical Approximation of the ELBO Gradient in the Context of the Clutter ProblemCode0
All-in-one simulation-based inferenceCode2
Leveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learningCode0
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Benchmark Results

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