SOTAVerified

Bayesian Inference

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

Papers

Showing 671680 of 2226 papers

TitleStatusHype
A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting0
A Markov Model of Machine Translation using Non-parametric Bayesian Inference0
Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning0
A Multi-armed Bandit MCMC, with applications in sampling from doubly intractable posterior0
Data augmentation in Bayesian neural networks and the cold posterior effect0
Adams Conditioning and Likelihood Ratio Transfer Mediated Inference0
Data-Informed Decomposition for Localized Uncertainty Quantification of Dynamical Systems0
Augmented Message Passing Stein Variational Gradient Descent0
Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier maps0
Big Learning with Bayesian Methods0
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Benchmark Results

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