SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1481–1490 of 2226 papers

TitleStatusHype
A Multilayered Block Network Model to Forecast Large Dynamic Transportation Graphs: an Application to US Air Transport—0
Transflow Learning: Repurposing Flow Models Without Retraining—0
Learning of Weighted Multi-layer Networks via Dynamic Social Spaces, with Application to Financial Interbank TransactionsCode0
Differentially Private Federated Variational InferenceCode0
Measuring Uncertainty through Bayesian Learning of Deep Neural Network StructureCode0
Iterative Construction of Gaussian Process Surrogate Models for Bayesian Inference—0
Improved algorithm for neuronal ensemble inference by Monte Carlo method—0
A Bayesian/Information Theoretic Model of Bias Learning—0
Streaming Bayesian Inference for Crowdsourced Classification—0
Combining human cell line transcriptome analysis and Bayesian inference to build trustworthy machine learning models for prediction of animal toxicity in drug development—0
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Benchmark Results

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