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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 81–90 of 2226 papers

TitleStatusHype
Physics-Informed Gaussian Process Regression Generalizes Linear PDE SolversCode1
Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive ModelsCode1
Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World SurveillanceCode1
Fast and robust Bayesian Inference using Gaussian Processes with GPryCode1
Convolutional Bayesian Kernel Inference for 3D Semantic MappingCode1
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian InferenceCode1
Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact caseCode1
Bayesian Inference with Latent Hamiltonian Neural NetworksCode1
Reliable amortized variational inference with physics-based latent distribution correctionCode1
Scalable Bayesian Inference for Detection and Deblending in Astronomical ImagesCode1
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Benchmark Results

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