17 citations · 21 across the 8 of their papers we have counts for
8 papers
From Discrete to Continuous: Deep Fair Clustering With Transferable Representations
Xiang Zhang
We consider the problem of deep fair clustering, which partitions data into clusters via the representations extracted by deep neural networks while hiding sensitive data attribute…
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-Series
Yihe Wang, Yu Han, Haishuai Wang +1
Contrastive representation learning is crucial in medical time series analysis as it alleviates dependency on labor-intensive, domain-specific, and scarce expert annotations. Howev…
Diff-Transfer: Model-based Robotic Manipulation Skill Transfer via Differentiable Physics Simulation
Yuqi Xiang, Feitong Chen, Qinsi Wang +5
The capability to transfer mastered skills to accomplish a range of similar yet novel tasks is crucial for intelligent robots. In this work, we introduce ,…
GC-Flow: A Graph-Based Flow Network for Effective Clustering
Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang +1
Graph convolutional networks (GCNs) are \emph{discriminative models} that directly model the class posterior for semi-supervised classification of graph data. Whi…
Self-Supervised Scene Dynamic Recovery from Rolling Shutter Images and Events
Yangguang Wang, Xiang Zhang, Mingyuan Lin +4
Scene Dynamic Recovery (SDR) by inverting distorted Rolling Shutter (RS) images to an undistorted high frame-rate Global Shutter (GS) video is a severely ill-posed problem due to t…
Recovering Continuous Scene Dynamics from A Single Blurry Image with Events
Zhangyi Cheng, Xiang Zhang, Lei Yu +3
This paper aims at demystifying a single motion-blurred image with events and revealing temporally continuous scene dynamics encrypted behind motion blurs. To achieve this end, an…