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 1741–1750 of 2226 papers

TitleStatusHype
Sprucing up the trees -- Error detection in treebanks—0
Towards identifying the optimal datasize for lexically-based Bayesian inference of linguistic phylogenies—0
Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliability—0
Automatic Bayesian Density Analysis—0
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard ModelCode0
Online Label Aggregation: A Variational Bayesian Approach—0
Bayesian filtering unifies adaptive and non-adaptive neural network optimization methodsCode0
Spatio-Temporal Structured Sparse Regression with Hierarchical Gaussian Process Priors—0
Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex ModelsCode0
A Driver Behavior Modeling Structure Based on Non-parametric Bayesian Stochastic Hybrid Architecture—0
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Benchmark Results

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