2 citations · 5 across the 9 of their papers we have counts for
6 papers · 1 filter
Adaptive Feature Interpolation for Low-Shot Image Generation
Mengyu Dai, Haibin Hang, Xiaoyang Guo
Training of generative models especially Generative Adversarial Networks can easily diverge in low-data setting. To mitigate this issue, we propose a novel implicit data augmentati…
Rethinking Multidimensional Discriminator Output for Generative Adversarial Networks
Mengyu Dai, Haibin Hang, Anuj Srivastava
The study of multidimensional discriminator (critic) output for Generative Adversarial Networks has been underexplored in the literature. In this paper, we generalize the Wasserste…
U-match factorization: sparse homological algebra, lazy cycle representatives, and dualities in persistent (co)homology
Haibin Hang, Chad Giusti, Lori Ziegelmeier +1
Persistent homology is a leading tool in topological data analysis (TDA). Many problems in TDA can be solved via homological -- and indeed, linear -- algebra. However, matrices in…
Detecting Carbon Nanotube Orientation with Topological Data Analysis of Scanning Electron Micrographs
Liyu Dong, Haibin Hang, Jin Gyu Park +2
As the aerospace industry becomes increasingly demanding for stronger lightweight materials, the ultra-strong carbon nanotube (CNT) composites with highly aligned CNT network struc…
Manifold Matching via Deep Metric Learning for Generative Modeling
Mengyu Dai, Haibin Hang
We propose a manifold matching approach to generative models which includes a distribution generator (or data generator) and a metric generator. In our framework, we view the real…
Decorated Merge Trees for Persistent Topology
Justin Curry, Haibin Hang, Washington Mio +2
This paper introduces decorated merge trees (DMTs) as a novel invariant for persistent spaces. DMTs combine both and information into a single data structure that disti…