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 941–950 of 2226 papers

TitleStatusHype
pymdp: A Python library for active inference in discrete state spacesCode2
Loss-calibrated expectation propagation for approximate Bayesian decision-making—0
SpectraNet: Learned Recognition of Artificial Satellites From High Contrast Spectroscopic Imagery—0
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband ItemsCode0
Classifying Turbulent Environments via Machine Learning—0
Bayesian Invariant Risk Minimization—0
Inferring perceptual decision making parameters from behavior in production and reproduction tasks—0
Interpreting Dynamical Systems as Bayesian Reasoners—0
Reactive Message Passing for Scalable Bayesian InferenceCode1
Bayesian Approaches to Shrinkage and Sparse EstimationCode0
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Benchmark Results

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