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 721–730 of 2226 papers

TitleStatusHype
A compartmental model for Xylella fastidiosa diseases with explicit vector seasonal dynamics—0
Designing Perceptual Puzzles by Differentiating Probabilistic Programs—0
DART: Depth-Enhanced Accurate and Real-Time Background Matting—0
Data augmentation in Bayesian neural networks and the cold posterior effect—0
Data fission: splitting a single data point—0
Bayesian data fusion with shared priors—0
Physics-constrained Bayesian inference of state functions in classical density-functional theory—0
Data-Driven Verification under Signal Temporal Logic Constraints—0
Data-Informed Decomposition for Localized Uncertainty Quantification of Dynamical Systems—0
Biases and Variability from Costly Bayesian Inference—0
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Benchmark Results

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