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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 501–510 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Parsimony-Enhanced Sparse Bayesian Learning for Robust Discovery of Partial Differential Equations	Jul 8, 2021	Bayesian InferenceModel Selection	CodeCode Available	0	5
Amortized Bayesian inference for clustering models	Nov 24, 2018	Bayesian InferenceClustering	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
Deep Learning and genetic algorithms for cosmological Bayesian inference speed-up	May 6, 2024	Bayesian InferenceHyperparameter Optimization	CodeCode Available	0	5
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in Kenya	May 31, 2023	Bayesian Inference	CodeCode Available	0	5
Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active Inference	Sep 30, 2024	Bayesian InferenceContinual Learning	CodeCode Available	0	5
Differentially Private Bayesian Learning on Distributed Data	Mar 3, 2017	Bayesian Inference	CodeCode Available	0	5
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	CodeCode Available	0	5
deBInfer: Bayesian inference for dynamical models of biological systems in R	Oct 15, 2016	Bayesian Inference	CodeCode Available	0	5
Deep Bayesian inference for seismic imaging with tasks	Oct 10, 2021	Bayesian InferenceInductive Bias	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