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 511–520 of 2226 papers

TitleStatusHype
Bayesian Boosting for Linear Mixed Models—0
Analog Seizure Detection for Implanted Responsive Neurostimulation—0
Beta Residuals: Improving Fault-Tolerant Control for Sensory Faults via Bayesian Inference and Precision Learning—0
Bayesian Bandit Algorithms with Approximate Inference in Stochastic Linear Bandits—0
Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models—0
Absolute Ranking: An Essential Normalization for Benchmarking Optimization Algorithms—0
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification—0
Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence—0
Belief patterns with information processing—0
Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference—0
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Benchmark Results

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