174 citations · 191 across the 7 of their papers we have counts for
7 papers
Tensor Completion Leveraging Graph Information: A Dynamic Regularization Approach with Statistical Guarantees
Kaidong Wang, Qianxin Yi, Yao Wang +3
We consider the problem of tensor completion with graphs serving as side information to represent interrelationships among variables. Existing approaches suffer from several limita…
Deep Generative Learning via Schrödinger Bridge
Gefei Wang, Yuling Jiao, Qian Xu +2
We propose to learn a generative model via entropy interpolation with a Schrödinger Bridge. The generative learning task can be formulated as interpolating between a reference dist…
Wasserstein-Wasserstein Auto-Encoders
Shunkang Zhang, Yuan Gao, Yuling Jiao +3
To address the challenges in learning deep generative models (e.g.,the blurriness of variational auto-encoder and the instability of training generative adversarial networks, we pr…
Deep Generative Learning via Variational Gradient Flow
Yuan Gao, Yuling Jiao, Yang Wang +3
We propose a general framework to learn deep generative models via \textbf{V}ariational \textbf{Gr}adient Fl\textbf{ow} (VGrow) on probability spaces. The evolving distribution tha…
Mathematical design of a novel gesture-based instruction/input device using wave detection
Hongyu Liu, Yuliang Wang, Can Yang
In this paper, we present a conceptual design of a novel gesture-based instruction/input device using wave detection. The device recogonizes/detects gestures from a person and base…
Total Variation Regularized Tensor RPCA for Background Subtraction from Compressive Measurements
Wenfei Cao, Yao Wang, Jian Sun +4
Background subtraction has been a fundamental and widely studied task in video analysis, with a wide range of applications in video surveillance, teleconferencing and 3D modeling.…
Low-Rank Modeling and Its Applications in Image Analysis
Xiaowei Zhou, Can Yang, Hongyu Zhao +1
Low-rank modeling generally refers to a class of methods that solve problems by representing variables of interest as low-rank matrices. It has achieved great success in various fi…