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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 2011–2020 of 2226 papers

Title	Date	Tasks	Status	Hype
Robust Optimisation Monte Carlo	Apr 1, 2019	Bayesian Inference	CodeCode Available	0
Neural Tangents: Fast and Easy Infinite Neural Networks in Python	Dec 5, 2019	Bayesian InferenceCPU	CodeCode Available	0
Bayesian inference of species trees using diffusion models	Sep 16, 2019	Bayesian Inference	CodeCode Available	0
Fuzzy Bayesian Learning	Oct 28, 2016	Bayesian InferenceGeneral Classification	CodeCode Available	0
Bayesian task embedding for few-shot Bayesian optimization	Jan 2, 2020	Bayesian InferenceBayesian Optimization	CodeCode Available	0
Attentional Prototype Inference for Few-Shot Segmentation	May 14, 2021	Bayesian InferenceFew-Shot Semantic Segmentation	CodeCode Available	0
Efficient Training of Probabilistic Neural Networks for Survival Analysis	Apr 9, 2024	Bayesian InferenceComputational Efficiency	CodeCode Available	0
Robust probabilistic inference via a constrained transport metric	Mar 17, 2023	Bayesian Inference	CodeCode Available	0
Neuron's Eye View: Inferring Features of Complex Stimuli from Neural Responses	Dec 4, 2015	Bayesian InferenceState Space Models	CodeCode Available	0
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems	Apr 17, 2023	Bayesian InferenceComputed Tomography (CT)	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