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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 1931–1940 of 2226 papers

Title	Date	Tasks	Status	Hype
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition	May 28, 2019	Audio ClassificationBayesian Inference	CodeCode Available	0
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms	Oct 18, 2016	Bayesian InferenceStochastic Optimization	CodeCode Available	0
Black-box Coreset Variational Inference	Nov 4, 2022	Bayesian InferenceData Summarization	CodeCode Available	0
Stochastic Approximation with Biased MCMC for Expectation Maximization	Feb 27, 2024	Bayesian Inference	CodeCode Available	0
Stochastic Backpropagation and Approximate Inference in Deep Generative Models	Jan 16, 2014	Bayesian Inference	CodeCode Available	0
Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference	Nov 25, 2021	Bayesian InferenceDimensionality Reduction	CodeCode Available	0
Model selection and parameter inference in phylogenetics using Nested Sampling	Apr 10, 2018	Bayesian InferenceModel Selection	CodeCode Available	0
Faster MCMC for Gaussian Latent Position Network Models	Jun 13, 2020	Bayesian InferenceClustering	CodeCode Available	0
Variational Model Perturbation for Source-Free Domain Adaptation	Oct 19, 2022	Bayesian InferenceDomain Adaptation	CodeCode Available	0
A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning	Jun 16, 2023	Bayesian InferenceMeta-Learning	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