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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 781–790 of 2226 papers

TitleStatusHype
A Latent Space Theory for Emergent Abilities in Large Language Models—0
Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping—0
Playing it safe: information constrains collective betting strategies—0
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse ProblemsCode0
Bayesian Inference on Brain-Computer Interfaces via GLASSCode0
Bayesian Inference for Jump-Diffusion Approximations of Biochemical Reaction Networks—0
Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry—0
Cascaded Calibration of Mechatronic Systems via Bayesian Inference—0
A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas—0
Leveraging joint sparsity in hierarchical Bayesian learningCode0
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Benchmark Results

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