Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs. - Minjie Wang; Lingfan Yu; Da Zheng; Quan Gan; Yu Gai; Zihao Ye 001; Mufei Li; Jinjing Zhou; Qi Huang 001; Chao Ma 025; Ziyue Huang; Qipeng Guo; et al. (CoRR, 2019)

DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. - Da Zheng; Chao Ma 025; Minjie Wang; Jinjing Zhou; Qidong Su; Xiang Song 003; Quan Gan; Zheng Zhang 001; George Karypis (IA3@SC, 2020)

Graph Neural Networks Inspired by Classical Iterative Algorithms. - Yongyi Yang; Tang Liu; Yangkun Wang; Jinjing Zhou; Quan Gan; Zhewei Wei; Zheng Zhang 001; Zengfeng Huang; David Wipf (ICML, 2021)

DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science. - Mufei Li; Jinjing Zhou; Jiajing Hu; Wenxuan Fan; Yangkang Zhang; Yaxin Gu; George Karypis (CoRR, 2021)

DGI: Easy and Efficient Inference for GNNs. - Peiqi Yin; Xiao Yan 002; Jinjing Zhou; Qiang Fu; Zhenkun Cai; James Cheng; Bo Tang 016; Minjie Wang (CoRR, 2022)

DGI: An Easy and Efficient Framework for GNN Model Evaluation. - Peiqi Yin; Xiao Yan 002; Jinjing Zhou; Qiang Fu; Zhenkun Cai; James Cheng; Bo Tang 016; Minjie Wang (KDD, 2023)