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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 181–190 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive Models	Nov 23, 2022	Bayesian InferenceTime Series	CodeCode Available	1	5
Neural Variational Gradient Descent	Jul 22, 2021	Bayesian Inferenceregression	CodeCode Available	1	5
Accelerated Bayesian SED Modeling using Amortized Neural Posterior Estimation	Mar 14, 2022	Bayesian InferenceCPU	CodeCode Available	1	5
Bayesian Inference with Latent Hamiltonian Neural Networks	Aug 12, 2022	Bayesian Inference	CodeCode Available	1	5
Parallel Streaming Wasserstein Barycenters	May 21, 2017	Bayesian Inference	CodeCode Available	1	5
Particle-MALA and Particle-mGRAD: Gradient-based MCMC methods for high-dimensional state-space models	Jan 26, 2024	Bayesian InferenceState Space Models	CodeCode Available	1	5
Understanding and Accelerating Particle-Based Variational Inference	Jul 4, 2018	Bayesian InferenceVariational Inference	CodeCode Available	1	5
Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers	Dec 23, 2022	Bayesian Inferenceregression	CodeCode Available	1	5
Pick-and-Mix Information Operators for Probabilistic ODE Solvers	Oct 20, 2021	Bayesian Inference	CodeCode Available	1	5
Probabilistic Autoencoder	Jun 9, 2020	Bayesian InferenceDenoising	CodeCode Available	1	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