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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 71–80 of 2226 papers

TitleStatusHype
Variational multiple shooting for Bayesian ODEs with Gaussian processesCode1
A Probabilistic State Space Model for Joint Inference from Differential Equations and DataCode1
BayesFlow: Learning complex stochastic models with invertible neural networksCode1
Bayesian Adversarial Human Motion SynthesisCode1
Bayesian differential programming for robust systems identification under uncertaintyCode1
Bayesian Diffusion Models for 3D Shape ReconstructionCode1
A Primer on Bayesian Neural Networks: Review and DebatesCode1
Bayesian graph convolutional neural networks via tempered MCMCCode1
A Simple Baseline for Bayesian Uncertainty in Deep LearningCode1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric ApproachesCode1
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Benchmark Results

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