35 citations · 54 across the 5 of their papers we have counts for
9 papers
Bootstrapping Informative Graph Augmentation via A Meta Learning Approach
Hang Gao, Jiangmeng Li, Wenwen Qiang +3
Recent works explore learning graph representations in a self-supervised manner. In graph contrastive learning, benchmark methods apply various graph augmentation approaches. Howev…
Long-term Human Motion Prediction with Scene Context
Zhe Cao, Hang Gao, Karttikeya Mangalam +3
Human movement is goal-directed and influenced by the spatial layout of the objects in the scene. To plan future human motion, it is crucial to perceive the environment -- imagine…
Deep Learning on Knowledge Graph for Recommender System: A Survey
Yang Gao, Yi-Fan Li, Yu Lin +2
Recent advances in research have demonstrated the effectiveness of knowledge graphs (KG) in providing valuable external knowledge to improve recommendation systems (RS). A knowledg…
Using Neural Networks for Programming by Demonstration
Karan K. Budhraja, Hang Gao, Tim Oates
Agent-based modeling is a paradigm of modeling dynamic systems of interacting agents that are individually governed by specified behavioral rules. Training a model of such agents t…
Universal Adversarial Perturbation for Text Classification
Hang Gao, Tim Oates
Given a state-of-the-art deep neural network text classifier, we show the existence of a universal and very small perturbation vector (in the embedding space) that causes natural t…
Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation
Hang Gao, Xizhou Zhu, Steve Lin +1
Convolutional networks are not aware of an object's geometric variations, which leads to inefficient utilization of model and data capacity. To overcome this issue, recent works on…