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 1251–1260 of 2226 papers

TitleStatusHype
Softplus Regressions and Convex Polytopes—0
Solution of Physics-based Bayesian Inverse Problems with Deep Generative Priors—0
Solving Bongard Problems with a Visual Language and Pragmatic Reasoning—0
Solving Differential Equations Using Neural Network Solution Bundles—0
Solving #SAT and Bayesian Inference with Backtracking Search—0
Some Extensions of Probabilistic Logic—0
Sparse Bayesian Dictionary Learning with a Gaussian Hierarchical Model—0
Spatial Relation Graph and Graph Convolutional Network for Object Goal Navigation—0
Spatial Uncertainty Sampling for End-to-End Control—0
Spatial-variant causal Bayesian inference for rapid seismic ground failures and impacts estimation—0
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Benchmark Results

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