Roundtrip: A Deep Generative Neural Density Estimator

• URL: http://arxiv.org/abs/2004.09017v4
• Date: Fri, 4 Sep 2020 07:17:33 GMT
• Title: Roundtrip: A Deep Generative Neural Density Estimator
• Authors: Qiao Liu, Jiaze Xu, Rui Jiang, Wing Hung Wong
• Abstract summary: We propose Roundtrip as a general-purpose neural density estimator based on deep generative models. In a series of experiments, Roundtrip achieves state-of-the-art performance in a diverse range of density estimation tasks.
• Score: 6.704101978104295
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Density estimation is a fundamental problem in both statistics and machine learning. In this study, we proposed Roundtrip as a general-purpose neural density estimator based on deep generative models. Roundtrip retains the generative power of generative adversarial networks (GANs) but also provides estimates of density values. Unlike previous neural density estimators that put stringent conditions on the transformation from the latent space to the data space, Roundtrip enables the use of much more general mappings. In a series of experiments, Roundtrip achieves state-of-the-art performance in a diverse range of density estimation tasks.

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