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 1721–1730 of 2226 papers

TitleStatusHype
BAR: Bayesian Activity Recognition using variational inference—0
BARNN: A Bayesian Autoregressive and Recurrent Neural Network—0
Barrier Certificates for Unknown Systems with Latent States and Polynomial Dynamics using Bayesian Inference—0
BAT.jl -- A Julia-based tool for Bayesian inference—0
BayesAdapter: enhanced uncertainty estimation in CLIP few-shot adaptation—0
Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning—0
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting—0
Bayesian Approaches for Revealing Complex Neural Network Dynamics in Parkinson's Disease—0
Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models—0
Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits—0
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Benchmark Results

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