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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 151–160 of 2226 papers

Title	Date	Tasks	Status	Hype
Encoding the latent posterior of Bayesian Neural Networks for uncertainty quantification	Dec 4, 2020	Bayesian InferenceDecision Making Under Uncertainty	CodeCode Available	1
Towards constraining warm dark matter with stellar streams through neural simulation-based inference	Nov 30, 2020	Bayesian Inference	CodeCode Available	1
Simulation-efficient marginal posterior estimation with swyft: stop wasting your precious time	Nov 27, 2020	AstronomyBayesian Inference	CodeCode Available	1
Enriching ImageNet with Human Similarity Judgments and Psychological Embeddings	Nov 22, 2020	Bayesian InferenceObject Recognition	CodeCode Available	1
Transforming Gaussian Processes With Normalizing Flows	Nov 3, 2020	Bayesian InferenceGaussian Processes	CodeCode Available	1
Bayesian Deep Learning via Subnetwork Inference	Oct 28, 2020	Bayesian InferenceDeep Learning	CodeCode Available	1
OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany	Oct 1, 2020	Bayesian InferenceEpidemiology	CodeCode Available	1
TensorBNN: Bayesian Inference for Neural Networks using Tensorflow	Sep 30, 2020	Bayesian InferenceGPU	CodeCode Available	1
Federated Generalized Bayesian Learning via Distributed Stein Variational Gradient Descent	Sep 11, 2020	Bayesian InferenceFederated Learning	CodeCode Available	1
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning	Sep 4, 2020	Bayesian InferenceFederated Learning	CodeCode Available	1

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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