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 1781–1790 of 2226 papers

TitleStatusHype
Bayesian Joint Spike-and-Slab Graphical LassoCode0
Wasserstein Measure Coresets—0
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive FlowsCode1
Spatial Uncertainty Sampling for End-to-End Control—0
Improving Predictive Uncertainty Estimation using Dropout -- Hamiltonian Monte Carlo—0
Subsampling Sequential Monte Carlo for Static Bayesian Models—0
Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in BadlandsCode0
A Channel-based Exact Inference Algorithm for Bayesian Networks—0
A sequential sampling strategy for extreme event statistics in nonlinear dynamical systems—0
Solving Bongard Problems with a Visual Language and Pragmatic Reasoning—0
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Benchmark Results

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