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 1031–1040 of 2226 papers

TitleStatusHype
Distributed Bayesian inference for consistent labeling of tracked objects in non-overlapping camera networks—0
Bayesian inference for bivariate ranks—0
Bayesian Inference by Symbolic Model Checking—0
Distilling Calibration via Conformalized Credal Inference—0
Bayesian inference as iterated random functions with applications to sequential inference in graphical models—0
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting—0
Bayesian inference as a cross-linguistic word segmentation strategy: Always learning useful things—0
A normative theory of social conflict—0
A Deep Learning Approach to Dst Index Prediction—0
Discriminative Relational Topic Models—0
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Benchmark Results

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