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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 41–50 of 2226 papers

TitleStatusHype
BayesDLL: Bayesian Deep Learning LibraryCode1
BayesFlow: Learning complex stochastic models with invertible neural networksCode1
Bayesian continual learning and forgetting in neural networksCode1
Bayesian differential programming for robust systems identification under uncertaintyCode1
Accelerated Bayesian SED Modeling using Amortized Neural Posterior EstimationCode1
Understanding and Accelerating Particle-Based Variational InferenceCode1
Bayesian inference for logistic models using Polya-Gamma latent variablesCode1
Variational multiple shooting for Bayesian ODEs with Gaussian processesCode1
Bayesian neural networks via MCMC: a Python-based tutorialCode1
Bayesian graph convolutional neural networks via tempered MCMCCode1
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Benchmark Results

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