activity
20172022
most citedMulti-Target, Multi-Camera Tracking by Hierarchical Clustering: Recent Progress on DukeMTMC Project

65 citations · 192 across the 9 of their papers we have counts for

collaborators

10 papers

cs.LG202230 cited

Domain Knowledge-Infused Deep Learning for Automated Analog/Radio-Frequency Circuit Parameter Optimization

Weidong Cao, Mouhacine Benosman, Xuan Zhang +1

The design automation of analog circuits is a longstanding challenge. This paper presents a reinforcement learning method enhanced by graph learning to automate the analog circuit…

cs.LG20226 cited

Domain Knowledge-Based Automated Analog Circuit Design with Deep Reinforcement Learning

Weidong Cao, Mouhacine Benosman, Xuan Zhang +1

The design automation of analog circuits is a longstanding challenge in the integrated circuit field. This paper presents a deep reinforcement learning method to expedite the desig…

cs.LG20216 cited

Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs

Zhao Xu, Youzhi Luo, Xuan Zhang +7

Graph neural networks are emerging as promising methods for modeling molecular graphs, in which nodes and edges correspond to atoms and chemical bonds, respectively. Recent studies…

cs.CV202155 cited

LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation

Guoping Xu, Xingrong Wu, Xuan Zhang +1

Medical image segmentation plays an essential role in developing computer-assisted diagnosis and therapy systems, yet still faces many challenges. In the past few years, the popula…

cs.LG20215 cited

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks

Meng Liu, Cong Fu, Xuan Zhang +7

Molecular property prediction is gaining increasing attention due to its diverse applications. One task of particular interests and importance is to predict quantum chemical proper…

cs.CL2021

Sent2Matrix: Folding Character Sequences in Serpentine Manifolds for Two-Dimensional Sentence

Hongyang Gao, Yi Liu, Xuan Zhang +1

We study text representation methods using deep models. Current methods, such as word-level embedding and character-level embedding schemes, treat texts as either a sequence of ato…