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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 171–180 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Inferring COVID-19 spreading rates and potential change points for case number forecasts	Apr 2, 2020	Bayesian Inference	CodeCode Available	1	5
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo	Oct 14, 2019	Bayesian Inference	CodeCode Available	1	5
Bayesian hierarchical stacking: Some models are (somewhere) useful	Jan 22, 2021	Bayesian InferenceTime Series	CodeCode Available	1	5
Laplacian Autoencoders for Learning Stochastic Representations	Jun 30, 2022	Bayesian InferenceOut-of-Distribution Detection	CodeCode Available	1	5
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning	Feb 11, 2019	Bayesian InferenceDeep Learning	CodeCode Available	1	5
Diffusive Gibbs Sampling	Feb 5, 2024	Bayesian InferenceDenoising	CodeCode Available	1	5
Low-rank extended Kalman filtering for online learning of neural networks from streaming data	May 31, 2023	Bayesian InferenceVariational Inference	CodeCode Available	1	5
Memory-Based Meta-Learning on Non-Stationary Distributions	Feb 6, 2023	Bayesian InferenceMeta-Learning	CodeCode Available	1	5
Particle Flow Bayes' Rule	Feb 2, 2019	Bayesian InferenceMeta-Learning	CodeCode Available	1	5
Flexible Bayesian Nonlinear Model Configuration	Mar 5, 2020	Bayesian Inferencemodel	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