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 131–140 of 2226 papers

TitleStatusHype
Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlasCode1
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical ImagingCode1
Bayesian graph convolutional neural networks via tempered MCMCCode1
ComBiNet: Compact Convolutional Bayesian Neural Network for Image SegmentationCode1
Learning by example: fast reliability-aware seismic imaging with normalizing flowsCode1
D3p -- A Python Package for Differentially-Private Probabilistic ProgrammingCode1
A Probabilistic State Space Model for Joint Inference from Differential Equations and DataCode1
Modeling tail risks of inflation using unobserved component quantile regressionsCode1
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy dataCode1
A practical tutorial on Variational BayesCode1
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Benchmark Results

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