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 1641–1650 of 2226 papers

TitleStatusHype
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation—0
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization—0
Localized Schrödinger Bridge Sampler—0
Localizing Bugs in Program Executions with Graphical Models—0
Locally Adaptive Bayesian Multivariate Time Series—0
Locally adaptive factor processes for multivariate time series—0
Locally Differentially Private Bayesian Inference—0
Location Tracking for Reconfigurable Intelligent Surfaces Aided Vehicle Platoons: Diverse Sparsities Inspired Approaches—0
Locking and Quacking: Stacking Bayesian model predictions by log-pooling and superposition—0
Looking at the posterior: accuracy and uncertainty of neural-network predictions—0
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Benchmark Results

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