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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 1391–1400 of 2226 papers

TitleStatusHype
Faster MCMC for Gaussian Latent Position Network ModelsCode0
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization—0
Approximate Inference for Spectral Mixture Kernel—0
Detecting structural perturbations from time series with deep learningCode0
A Variational View on Bootstrap Ensembles as Bayesian Inference—0
Analogy as Nonparametric Bayesian Inference over Relational Systems—0
Linguists Who Use Probabilistic Models Love Them: Quantification in Functional Distributional Semantics—0
Variational Bayesian Inference for Crowdsourcing Predictions—0
Adaptive quadrature schemes for Bayesian inference via active learning—0
QuLBIT: Quantum-Like Bayesian Inference Technologies for Cognition and Decision—0
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Benchmark Results

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