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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 51–60 of 2226 papers

Title	Date	Tasks	Status	Hype
A Bayesian algorithm for retrosynthesis	Mar 6, 2020	Bayesian InferenceCombinatorial Optimization	CodeCode Available	1
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context Learning	May 3, 2024	Bayesian InferenceIn-Context Learning	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
Complete parameter inference for GW150914 using deep learning	Aug 7, 2020	Bayesian InferenceDeep Learning	CodeCode Available	1
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reduction	Jun 8, 2021	Bayesian InferenceDimensionality Reduction	CodeCode Available	1
Continual Learning via Sequential Function-Space Variational Inference	Dec 28, 2023	Bayesian InferenceContinual Learning	CodeCode Available	1
Convolutional Bayesian Kernel Inference for 3D Semantic Mapping	Sep 21, 2022	Bayesian Inference	CodeCode Available	1
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning	Feb 11, 2019	Bayesian InferenceDeep Learning	CodeCode Available	1
Bayesian graph convolutional neural networks via tempered MCMC	Apr 17, 2021	Bayesian InferenceDeep Learning	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