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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 151–160 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Automatic Posterior Transformation for Likelihood-Free Inference	May 17, 2019	Bayesian InferenceTime Series	CodeCode Available	1	5
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning	Jun 6, 2015	Bayesian InferenceDeep Reinforcement Learning	CodeCode Available	1	5
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets	Feb 8, 2023	Bayesian InferenceCausal Discovery	CodeCode Available	1	5
Amortized Monte Carlo Integration	Jul 18, 2019	Bayesian Inference	CodeCode Available	1	5
Automatic Rao-Blackwellization for Sequential Monte Carlo with Belief Propagation	Dec 15, 2023	Bayesian InferenceState Space Models	CodeCode Available	1	5
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification	Dec 4, 2020	Bayesian InferenceDecision Making Under Uncertainty	CodeCode Available	1	5
Eryn : A multi-purpose sampler for Bayesian inference	Mar 3, 2023	AstronomyBayesian Inference	CodeCode Available	1	5
Triple equivalence for the emergence of biological intelligence	Sep 7, 2024	Bayesian InferenceModel Selection	CodeCode Available	1	5
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty	May 9, 2021	Bayesian InferenceDomain Generalization	CodeCode Available	1	5
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference	Oct 17, 2023	Bayesian InferenceImage Generation	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