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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 411–420 of 2226 papers

TitleStatusHype
Stein Variational Newton Neural Network EnsemblesCode0
Interacting Large Language Model Agents. Interpretable Models and Social Learning—0
Constrained Sampling with Primal-Dual Langevin Monte CarloCode0
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data CorruptionsCode0
KALAM: toolKit for Automating high-Level synthesis of Analog computing systeMs—0
Full-waveform earthquake source inversion using simulation-based inferenceCode0
Bayesian Approaches for Revealing Complex Neural Network Dynamics in Parkinson's Disease—0
ELBOing Stein: Variational Bayes with Stein Mixture InferenceCode0
Variational Bayes Decomposition for Inverse Estimation with Superimposed Multispectral Intensity—0
A Stein Gradient Descent Approach for Doubly Intractable Distributions—0
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Benchmark Results

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