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 831–840 of 2226 papers

TitleStatusHype
Approximate Decentralized Bayesian Inference—0
Advancing Autonomous Vehicle Safety: A Combined Fault Tree Analysis and Bayesian Network Approach—0
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over the Simplex—0
A Bayesian model for identifying hierarchically organised states in neural population activity—0
A Bayesian Analysis of Dynamics in Free Recall—0
Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization—0
Bayesian inference of composition-dependent phase diagrams—0
Bayesian Inference of Bijective Non-Rigid Shape Correspondence—0
Approximate Bayesian inference in spatial environments—0
Advancing Audio Emotion and Intent Recognition with Large Pre-Trained Models and Bayesian Inference—0
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Benchmark Results

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