variational family
EigenVI: score-based variational inference with orthogonal function expansions
We develop EigenVI, an eigenvalue-based approach for black-box variational inference (BBVI).
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- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (1.00)
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- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.92)
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On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making
We compute the convergence rates of the RSVB approximate posterior and the corresponding optimal value.
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- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.92)
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- Information Technology > Modeling & Simulation (0.68)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.67)
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- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (1.00)
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- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.46)
Copula-like Variational Inference
Marcel Hirt, Petros Dellaportas, Alain Durmus
Neural Information Processing Systems http://nips.cc/
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- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Regression (0.48)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (0.46)
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Variational Inference with Gaussian Score Matching
V ariational inference (VI) is a method to approximate the computationally intractable posterior distributions that arise in Bayesian statistics.
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