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 1311–1320 of 2226 papers

TitleStatusHype
Subspace Constrained Variational Bayesian Inference for Structured Compressive Sensing with a Dynamic Grid—0
Surprise Calibration for Better In-Context Learning—0
Surrogate Likelihoods for Variational Annealed Importance Sampling—0
SwISS: A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy—0
Switching Linear Dynamics for Variational Bayes Filtering—0
Symbolic Analysis-based Reduced Order Markov Modeling of Time Series Data—0
Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-Dimensional Data-Driven Priors for Inverse Problems—0
TapType: Ten-finger text entry on everyday surfaces via Bayesian inference—0
Taxonomy, Structure, and Implementation of Evidential Reasoning—0
Tensor Regression Meets Gaussian Processes—0
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Benchmark Results

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