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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 721–730 of 2226 papers

TitleStatusHype
Orthogonal Polynomials Approximation Algorithm (OPAA):a functional analytic approach to estimating probability densities—0
Understanding Approximation for Bayesian Inference in Neural Networks—0
Bayesian score calibration for approximate modelsCode0
Generalization of generative model for neuronal ensemble inference method—0
Fully Bayesian inference for latent variable Gaussian process modelsCode0
Black-box Coreset Variational InferenceCode0
Fast and robust Bayesian Inference using Gaussian Processes with GPryCode1
Ensemble transport smoothing. Part I: Unified frameworkCode0
Ensemble transport smoothing. Part II: Nonlinear updatesCode0
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms—0
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Benchmark Results

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