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 1571–1580 of 2226 papers

TitleStatusHype
Adversarial Message Passing For Graphical Models—0
A Factor Graph Model of Trust for a Collaborative Multi-Agent System—0
A theory of representation learning gives a deep generalisation of kernel methods—0
Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in Neural Networks—0
A Formal Calculus for International Relations Computation and Evaluation—0
A Generalization Bound for Online Variational Inference—0
A Generative Modeling Framework for Inferring Families of Biomechanical Constitutive Laws in Data-Sparse Regimes—0
A Gibbs Sampler for Efficient Bayesian Inference in Sign-Identified SVARs—0
A Group-Wise Narrow Beam Design for Uplink Channel Estimation in Hybrid Beamforming Systems—0
A hierarchical Bayesian model for syntactic priming—0
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Benchmark Results

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