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stat.ML2019
Monte Carlo Gradient Estimation in Machine Learning
Shakir Mohamed, Mihaela Rosca, Michael Figurnov +1
This paper is a broad and accessible survey of the methods we have at our disposal for Monte Carlo gradient estimation in machine learning and across the statistical sciences: the…
stat.ML2018
Variational Autoencoder with Arbitrary Conditioning
Oleg Ivanov, Michael Figurnov, Dmitry Vetrov
We propose a single neural probabilistic model based on variational autoencoder that can be conditioned on an arbitrary subset of observed features and then sample the remaining fe…