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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 2161–2170 of 2226 papers

Title	Date	Tasks	Status	Hype
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models	Jul 11, 2024	Bayesian Inference	CodeCode Available	0
On the Expressiveness of Approximate Inference in Bayesian Neural Networks	Sep 2, 2019	Active LearningBayesian Inference	CodeCode Available	0
Information limits and Thouless-Anderson-Palmer equations for spiked matrix models with structured noise	May 31, 2024	Bayesian Inference	CodeCode Available	0
Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse	Dec 1, 2019	Bayesian InferenceDescriptive	CodeCode Available	0
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization	Dec 3, 2020	Bayesian Inference	CodeCode Available	0
Sensitivity-Aware Amortized Bayesian Inference	Oct 17, 2023	Bayesian InferenceDecision Making	CodeCode Available	0
Amortized Variational Inference: When and Why?	Jul 20, 2023	Bayesian InferenceGaussian Processes	CodeCode Available	0
Novel and flexible parameter estimation methods for data-consistent inversion in mechanistic modeling	Sep 17, 2020	Bayesian Inferenceparameter estimation	CodeCode Available	0
Variational Sequential Monte Carlo	May 31, 2017	Bayesian InferenceState Space Models	CodeCode Available	0
Interactive Learning of Physical Object Properties Through Robot Manipulation and Database of Object Measurements	Apr 10, 2024	Bayesian InferenceObject	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