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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 2041–2050 of 2226 papers

TitleStatusHype
Variational Inference based on Robust DivergencesCode0
Nonparametric Bayesian Deep Networks with Local CompetitionCode0
Generalized Posteriors in Approximate Bayesian ComputationCode0
Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-RiskCode0
AutoElicit: Using Large Language Models for Expert Prior Elicitation in Predictive ModellingCode0
Generalized Variational Inference: Three arguments for deriving new PosteriorsCode0
We Know Where We Don't Know: 3D Bayesian CNNs for Credible Geometric UncertaintyCode0
Sampling with Trusthworthy Constraints: A Variational Gradient FrameworkCode0
Bayesian Floor Field: Transferring people flow predictions across environmentsCode0
Generative Diffusion Receivers: Achieving Pilot-Efficient MIMO-OFDM CommunicationsCode0
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Benchmark Results

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