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 661–670 of 2226 papers

TitleStatusHype
Bilinear Subspace Variational Bayesian Inference for Joint Scattering Environment Sensing and Data Recovery in ISAC Systems—0
Compositional amortized inference for large-scale hierarchical Bayesian models—0
A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting—0
Active recursive Bayesian inference using Rényi information measures—0
A Markov Model of Machine Translation using Non-parametric Bayesian Inference—0
Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference—0
Augmented Message Passing Stein Variational Gradient Descent—0
Compressed particle methods for expensive models with application in Astronomy and Remote Sensing—0
Big Learning with Bayesian Methods—0
A majorization-minimization algorithm for nonnegative binary matrix factorization—0
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Benchmark Results

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