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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 161–170 of 2226 papers

TitleStatusHype
Bayesian graph convolutional neural networks via tempered MCMCCode1
Flexible Bayesian Nonlinear Model ConfigurationCode1
BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy imagesCode1
Amortized Monte Carlo IntegrationCode1
Full-Information Estimation of Heterogeneous Agent Models Using Macro and Micro DataCode1
Amortizing intractable inference in large language modelsCode1
Can Transformers Learn Full Bayesian Inference in Context?Code1
Bayesian differential programming for robust systems identification under uncertaintyCode1
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy dataCode1
CoS: Enhancing Personalization and Mitigating Bias with Context SteeringCode1
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Benchmark Results

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