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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 531–540 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	CodeCode Available	0	5
A Bayesian Approach for Medical Inquiry and Disease Inference in Automated Differential Diagnosis	Oct 15, 2021	Bayesian InferenceExperimental Design	CodeCode Available	0	5
ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition	Jun 8, 2025	Active LearningBayesian Inference	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
Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active Inference	Sep 30, 2024	Bayesian InferenceContinual Learning	CodeCode Available	0	5
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems	May 28, 2019	Bayesian InferenceZero-Shot Learning	CodeCode Available	0	5
A Compact Representation for Bayesian Neural Networks By Removing Permutation Symmetry	Dec 31, 2023	Bayesian InferenceVariational Inference	CodeCode Available	0	5
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks	Dec 16, 2015	Bayesian InferenceDeep Learning	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