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 1241–1250 of 2226 papers

TitleStatusHype
Simplifying deflation for non-convex optimization with applications in Bayesian inference and topology optimization—0
Simulating how animals learn: a new modelling framework applied to the process of optimal foraging—0
Simulation-based Bayesian inference for robotic grasping—0
Simulation-based Bayesian inference for multi-fingered robotic grasping—0
Simulation-based Bayesian inference under model misspecification—0
Simulation-based inference with the Python Package sbijax—0
Simultaneous Estimation of Noise Variance and Number of Peaks in Bayesian Spectral Deconvolution—0
Sketching for Latent Dirichlet-Categorical Models—0
SMC Is All You Need: Parallel Strong Scaling—0
SoftBart: Soft Bayesian Additive Regression Trees—0
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Benchmark Results

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