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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 61–70 of 2226 papers

Title	Date	Tasks	Status	Hype
Neural Clustering Processes	Dec 28, 2018	Bayesian InferenceClustering	CodeCode Available	1
Discriminative Training of VBx Diarization	Oct 4, 2023	Bayesian Inference	CodeCode Available	1
BayesFlow: Learning complex stochastic models with invertible neural networks	Mar 13, 2020	Bayesian InferenceEpidemiology	CodeCode Available	1
Bayesian Adversarial Human Motion Synthesis	Jun 1, 2020	Bayesian InferenceData Augmentation	CodeCode Available	1
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference	Oct 17, 2023	Bayesian InferenceImage Generation	CodeCode Available	1
Automatic Rao-Blackwellization for Sequential Monte Carlo with Belief Propagation	Dec 15, 2023	Bayesian InferenceState Space Models	CodeCode Available	1
BayesDLL: Bayesian Deep Learning Library	Sep 22, 2023	Bayesian InferenceDeep Learning	CodeCode Available	1
Bayesian continual learning and forgetting in neural networks	Apr 18, 2025	Bayesian InferenceContinual Learning	CodeCode Available	1
A Primer on Bayesian Neural Networks: Review and Debates	Sep 28, 2023	Bayesian Inference	CodeCode Available	1
A Probabilistic State Space Model for Joint Inference from Differential Equations and Data	Mar 18, 2021	Bayesian Inference	CodeCode Available	1

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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