• Corpus ID: 211296419

# Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows

@article{Deng2020ModelingCS,
title={Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows},
author={Ruizhi Deng and B. Chang and Marcus A. Brubaker and Greg Mori and Andreas M. Lehrmann},
journal={ArXiv},
year={2020},
volume={abs/2002.10516}
}
• Published 24 February 2020
• Computer Science, Mathematics
• ArXiv
Normalizing flows transform a simple base distribution into a complex target distribution and have proved to be powerful models for data generation and density estimation. In this work, we propose a novel type of normalizing flow driven by a differential deformation of the Wiener process. As a result, we obtain a rich time series model whose observable process inherits many of the appealing properties of its base process, such as efficient computation of likelihoods and marginals. Furthermore…

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