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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 1741–1750 of 2226 papers

TitleStatusHype
Stochasticity from function -- why the Bayesian brain may need no noise—0
Predictive Collective Variable Discovery with Deep Bayesian ModelsCode0
Estimating Bayesian Optimal Treatment Regimes for Dichotomous Outcomes using Observational Data—0
Robustness Guarantees for Bayesian Inference with Gaussian ProcessesCode0
A Variational Observation Model of 3D Object for Probabilistic Semantic SLAM—0
Seeing Tree Structure from Vibration—0
Convolutional Graph Auto-encoder: A Deep Generative Neural Architecture for Probabilistic Spatio-temporal Solar Irradiance Forecasting—0
Differentially Private Bayesian Inference for Exponential FamiliesCode0
Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion—0
Semantic Information G Theory and Logical Bayesian Inference for Machine Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified