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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 821–830 of 2226 papers

TitleStatusHype
Personalized Federated Learning via Variational Bayesian InferenceCode1
Fidelity of Hyperbolic Space for Bayesian Phylogenetic InferenceCode0
How Adults Understand What Young Children Say—0
Calibrating Agent-based Models to Microdata with Graph Neural Networks—0
Variational Bayes Deep Operator Network: A data-driven Bayesian solver for parametric differential equations—0
PAVI: Plate-Amortized Variational Inference—0
Scalable Deep Gaussian Markov Random Fields for General GraphsCode1
On the safe use of prior densities for Bayesian model selection—0
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel RecombinationCode1
A Learning- and Scenario-based MPC Design for Nonlinear Systems in LPV Framework with Safety and Stability Guarantees—0
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Benchmark Results

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