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 551–560 of 2226 papers

TitleStatusHype
Scalable Data Assimilation with Message PassingCode0
BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models—0
Underdetermined DOA Estimation of Off-Grid Sources Based on the Generalized Double Pareto Prior—0
Neural Methods for Amortized Inference—0
Partial Identification of Heteroskedastic Structural VARs: Theory and Bayesian Inference—0
Analytical Approximation of the ELBO Gradient in the Context of the Clutter ProblemCode0
Leveraging viscous Hamilton-Jacobi PDEs for uncertainty quantification in scientific machine learningCode0
Bayesian Federated Model Compression for Communication and Computation Efficiency—0
Efficient Sound Field Reconstruction with Conditional Invertible Neural Networks—0
Interactive Learning of Physical Object Properties Through Robot Manipulation and Database of Object MeasurementsCode0
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Benchmark Results

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