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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 1531–1540 of 2226 papers

TitleStatusHype
Bayesian Graph Convolution LSTM for Skeleton Based Action Recognition—0
Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference—0
Non-Gaussian processes and neural networks at finite widths—0
Debiased Bayesian inference for average treatment effectsCode0
Refining the variational posterior through iterative optimization—0
Gaussian Process Meta-Representations Of Neural Networks—0
On the Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks—0
Meta-Learning for Variational Inference—0
Deep Bayesian Structure NetworksCode0
Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over the Simplex—0
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Benchmark Results

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