activity
20192021
most citedDistance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning

98 citations · 178 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG202135 cited

Chemical-Reaction-Aware Molecule Representation Learning

Hongwei Wang, Weijiang Li, Xiaomeng Jin +4

Molecule representation learning (MRL) methods aim to embed molecules into a real vector space. However, existing SMILES-based (Simplified Molecular-Input Line-Entry System) or GNN…

cs.CV2021

RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representation

En Yu, Zhuoling Li, Shoudong Han +1

Existing online multiple object tracking (MOT) algorithms often consist of two subtasks, detection and re-identification (ReID). In order to enhance the inference speed and reduce…

cs.LG202098 cited

Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning

Pan Li, Yanbang Wang, Hongwei Wang +1

Learning representations of sets of nodes in a graph is crucial for applications ranging from node-role discovery to link prediction and molecule classification. Graph Neural Netwo…

cs.CV202020 cited

MAT: Motion-Aware Multi-Object Tracking

Shoudong Han, Piao Huang, Hongwei Wang +4

Modern multi-object tracking (MOT) systems usually model the trajectories by associating per-frame detections. However, when camera motion, fast motion, and occlusion challenges oc…

cs.CV2020

Refinements in Motion and Appearance for Online Multi-Object Tracking

Piao Huang, Shoudong Han, Jun Zhao +4

Modern multi-object tracking (MOT) system usually involves separated modules, such as motion model for location and appearance model for data association. However, the compatible p…

cs.LG201925 cited

Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems

Hongwei Wang, Fuzheng Zhang, Mengdi Zhang +4

Knowledge graphs capture structured information and relations between a set of entities or items. As such knowledge graphs represent an attractive source of information that could…