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Neural Ordinary Differential Equations for Continuous Normalizing Flows
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  • title: Householder meets Sylvester: Normalizing Flows for Variational Inference
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            Householder meets Sylvester: Normalizing Flows for Variational Inference
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            Householder meets Sylvester: Normalizing Flows for Variational Inference

            Jun 15, 2019

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            JT

            Jakub Tomczak

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            Invertible neural networks have been a significant thread of research in the ICML community for several years. Such transformations can offer a range of unique benefits: (1) They preserve information, allowing perfect reconstruction (up to numerical limits) and obviating the need to store hidden activations in memory for backpropagation. (2) They are often designed to track the changes in probability density that applying the transformation induces (as in normalizing flows). (3) Like autoreg…

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            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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