Wasserstein Learning of Deep Generative Point Process Models

23 May 2017

Papers citing "Wasserstein Learning of Deep Generative Point Process Models"

5 / 5 papers shown

Title
Neural Spatiotemporal Point Processes: Trends and Challenges Sumantrak Mukherjee Mouad Elhamdi George Mohler David Selby Yao Xie Sebastian Vollmer Gerrit Grossmann AI4TS 370 1 0 13 Feb 2025
Differentiable Adversarial Attacks for Marked Temporal Point Processes Pritish Chakraborty Vinayak Gupta R. Raj Srikanta J. Bedathur A. De AAML 416 0 0 17 Jan 2025
Recurrent Neural Goodness-of-Fit Test for Time Series Aoran Zhang Wenbin Zhou Liyan Xie Shixiang Zhu 52 1 0 17 Oct 2024
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 139 9,509 0 31 Mar 2017
Towards Principled Methods for Training Generative Adversarial Networks Martín Arjovsky M. Nault GAN 74 2,102 0 17 Jan 2017