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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 2071–2080 of 2226 papers

Title	Date	Tasks	Status	Hype
Gradient-Free Adversarial Attacks for Bayesian Neural Networks	Dec 23, 2020	Adversarial RobustnessBayesian Inference	CodeCode Available	0
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families	Jun 8, 2015	Bayesian Inference	CodeCode Available	0
Grammar Induction for Minimalist Grammars using Variational Bayesian Inference : A Technical Report	Oct 31, 2017	Bayesian Inferenceparameter estimation	CodeCode Available	0
Graph-based sequential beamforming	Aug 26, 2022	Bayesian Inference	CodeCode Available	0
Variational Inference for Bayesian Neural Networks under Model and Parameter Uncertainty	May 1, 2023	Bayesian InferenceVariational Inference	CodeCode Available	0
Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference	Jun 26, 2025	Bayesian InferenceUncertainty Quantification	CodeCode Available	0
A General Framework for Uncertainty Estimation in Deep Learning	Jul 16, 2019	Autonomous DrivingBayesian Inference	CodeCode Available	0
Scalable Data Assimilation with Message Passing	Apr 19, 2024	Bayesian InferenceGPU	CodeCode Available	0
Structured Stochastic Gradient MCMC	Jul 19, 2021	Bayesian InferenceVariational Inference	CodeCode Available	0
Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random Bases	Jun 18, 2015	Additive modelsBayesian Inference	CodeCode Available	0

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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