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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 741–750 of 2226 papers

TitleStatusHype
Logistic Variational Bayes RevisitedCode0
Robust probabilistic inference via a constrained transport metricCode0
Bayesian Model Selection for Identifying Markov Equivalent Causal Graphs—0
Bayesian Modeling of Motion Perception using Dynamical Stochastic Textures—0
A sampling-based circuit for optimal decision making—0
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport—0
Bayesian Methods in Automated Vehicle's Car-following Uncertainties: Enabling Strategic Decision Making—0
Array Partitioning Based Near-Field Attitude and Location Estimation—0
A Gibbs Sampler for Efficient Bayesian Inference in Sign-Identified SVARs—0
Bayesian Metaplasticity from Synaptic Uncertainty—0
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Benchmark Results

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