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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 301–310 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	CodeCode Available	0	5
Greedy inference with structure-exploiting lazy maps	May 31, 2019	Bayesian Inference	CodeCode Available	0	5
Empirical analysis of representation learning and exploration in neural kernel bandits	Nov 5, 2021	Bayesian InferenceDecision Making	CodeCode Available	0	5
Debiased Bayesian inference for average treatment effects	Sep 26, 2019	Bayesian InferenceCausal Inference	CodeCode Available	0	5
Deep Bayesian inference for seismic imaging with tasks	Oct 10, 2021	Bayesian InferenceInductive Bias	CodeCode Available	0	5
Deep Neural Networks as Gaussian Processes	Nov 1, 2017	Bayesian InferenceGaussian Processes	CodeCode Available	0	5
Bayesian Inference Gaussian Process Multiproxy Alignment of Continuous Signals (BIGMACS): Applications for Paleoceanography	Jul 20, 2019	Bayesian InferenceGPR	CodeCode Available	0	5
Fast Bayesian Inference for Neutrino Non-Standard Interactions at Dark Matter Direct Detection Experiments	May 23, 2024	Bayesian InferenceGPU	CodeCode Available	0	5
An embedded segmental K-means model for unsupervised segmentation and clustering of speech	Mar 23, 2017	Bayesian InferenceClustering	CodeCode Available	0	5
Projective Integral Updates for High-Dimensional Variational Inference	Jan 20, 2023	Bayesian InferenceVariational Inference	CodeCode Available	0	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