all AI news
Curvature Graph Generative Adversarial Networks. (arXiv:2203.01604v1 [cs.LG])
March 4, 2022, 2:11 a.m. | Jianxin Li, Xingcheng Fu, Qingyun Sun, Cheng Ji, Jiajun Tan, Jia Wu, Hao Peng
cs.LG updates on arXiv.org arxiv.org
Generative adversarial network (GAN) is widely used for generalized and
robust learning on graph data. However, for non-Euclidean graph data, the
existing GAN-based graph representation methods generate negative samples by
random walk or traverse in discrete space, leading to the information loss of
topological properties (e.g. hierarchy and circularity). Moreover, due to the
topological heterogeneity (i.e., different densities across the graph
structure) of graph data, they suffer from serious topological distortion
problems. In this paper, we proposed a novel Curvature …
More from arxiv.org / cs.LG updates on arXiv.org
Jobs in AI, ML, Big Data
Senior ML Researcher - 3D Geometry Processing | 3D Shape Generation | 3D Mesh Data
@ Promaton | Europe
Software Engineer, Data Platforms
@ Whatnot | San Francisco, CA, Los Angeles, CA, New York City, Phoenix, AZ, Seattle, WA, Denver, CO
Staff Data Engineer, Data Platform
@ Lilt | Indianapolis
Business Data Analyst - New Division
@ Breakthru Beverage Group | Toronto, ON, Canada
Data Operations Associate
@ iCapital | New York City, United States
Senior Data Scientist, R&D
@ Plusgrade | Toronto, Ontario