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 1301–1310 of 2226 papers

TitleStatusHype
Dimension reduction via score ratio matching—0
Dirichlet Bayesian Network Scores and the Maximum Relative Entropy Principle—0
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation—0
Discriminative Relational Topic Models—0
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting—0
Distilling Calibration via Conformalized Credal Inference—0
Distributed Bayesian inference for consistent labeling of tracked objects in non-overlapping camera networks—0
Distributed Bayesian Inference for Large-Scale IoT Systems—0
Distributed Variational Bayesian Algorithms Over Sensor Networks—0
Distributionally Robust Optimisation with Bayesian Ambiguity Sets—0
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Benchmark Results

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