activity
20182022
most citedGraph Contrastive Learning with Augmentations

866 citations · 1.8k across the 14 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

q-bio.BM2020

Cross-Modality Protein Embedding for Compound-Protein Affinity and Contact Prediction

Yuning You, Yang Shen

Compound-protein pairs dominate FDA-approved drug-target pairs and the prediction of compound-protein affinity and contact (CPAC) could help accelerate drug discovery. In this stud…

cs.LG2020★ 866 cited

Graph Contrastive Learning with Augmentations

Yuning You, Tianlong Chen, Yongduo Sui +3

Generalizable, transferrable, and robust representation learning on graph-structured data remains a challenge for current graph neural networks (GNNs). Unlike what has been develop…

cs.LG2020★ 65 cited

When Does Self-Supervision Help Graph Convolutional Networks?

Yuning You, Tianlong Chen, Zhangyang Wang +1

Self-supervision as an emerging technique has been employed to train convolutional neural networks (CNNs) for more transferrable, generalizable, and robust representation learning…

q-bio.MN2020

Network-principled deep generative models for designing drug combinations as graph sets

Mostafa Karimi, Arman Hasanzadeh, Yang shen

Combination therapy has shown to improve therapeutic efficacy while reducing side effects. Importantly, it has become an indispensable strategy to overcome resistance in antibiotic…

cs.LG2020★ 8 cited

L-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks

Yuning You, Tianlong Chen, Zhangyang Wang +1

Graph convolution networks (GCN) are increasingly popular in many applications, yet remain notoriously hard to train over large graph datasets. They need to compute node representa…