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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 601–610 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Deep Bayesian Structure Networks	Sep 25, 2019	Bayesian InferenceNeural Architecture Search	CodeCode Available	0	5
Black-box density function estimation using recursive partitioning	Oct 26, 2020	Bayesian Inference	CodeCode Available	0	5
Bayesian Pseudocoresets	Dec 1, 2020	Bayesian Inference	CodeCode Available	0	5
Blang: Bayesian declarative modelling of general data structures and inference via algorithms based on distribution continua	Dec 22, 2019	Bayesian Inference	CodeCode Available	0	5
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations	Jun 7, 2019	Bayesian InferenceVariational Inference	CodeCode Available	0	5
Deep Bayesian inference for seismic imaging with tasks	Oct 10, 2021	Bayesian InferenceInductive Bias	CodeCode Available	0	5
Deep surrogate accelerated delayed-acceptance HMC for Bayesian inference of spatio-temporal heat fluxes in rotating disc systems	Apr 5, 2022	Bayesian Inference	CodeCode Available	0	5
Dynamical Hyperspectral Unmixing with Variational Recurrent Neural Networks	Mar 19, 2023	Bayesian InferenceHyperspectral Unmixing	CodeCode Available	0	5
Automated Scalable Bayesian Inference via Hilbert Coresets	Oct 13, 2017	Bayesian Inference	CodeCode Available	0	5
Data-driven Approach for Interpolation of Sparse Data	May 2, 2025	Bayesian InferenceGaussian Processes	CodeCode Available	0	5

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	F-SWA	Accuracy	83.61	—	Unverified
2	F-SWAG	Accuracy	80.93	—	Unverified