Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models. - Guangyong Chen; Pengfei Chen 003; Chang-Yu Hsieh; Chee-Kong Lee; Benben Liao; Renjie Liao; Weiwen Liu; Jiezhong Qiu; Qiming Sun; Jie Tang 001; Richard S. Zemel; Shengyu Zhang 002 (CoRR, 2019)

ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. - Zhongkai Hao; Chengqiang Lu; Zhenya Huang; Hao Wang 076; Zheyuan Hu 002; Qi Liu 003; Enhong Chen; Cheekong Lee (KDD, 2020)

Motif-based Graph Self-Supervised Learning for Molecular Property Prediction. - Zaixi Zhang; Qi Liu 003; Hao Wang 076; Chengqiang Lu; Chee-Kong Lee (NeurIPS, 2021)

ProtGNN: Towards Self-Explaining Graph Neural Networks. - Zaixi Zhang; Qi Liu 003; Hao Wang 076; Chengqiang Lu; Cheekong Lee (AAAI, 2022)

Hierarchical Graph Transformer with Adaptive Node Sampling. - Zaixi Zhang; Qi Liu 003; Qingyong Hu; Chee-Kong Lee (NeurIPS, 2022)

Exploring the Dynamics of Quantum Information in Many-Body Localised Systems with High Performance Computing. - Shao-Hen Chiew; Leong-Chuan Kwek; Chee-Kong Lee (SCFA, 2022)

A photonic chip-based machine learning approach for the prediction of molecular properties. - Jonathan Wei Zhong Lau; Hui Zhang; Lingxiao Wan; Liang Shi; Hong Cai; Xianshu Luo; Patrick Lo; Chee-Kong Lee; Leong-Chuan Kwek; Ai Qun Liu (CoRR, 2022)

Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networks. - Yu-Qin Chen; Yu Chen; Chee-Kong Lee; Shengyu Zhang 002; Chang-Yu Hsieh (Nat. Mach. Intell., 2022)

An Equivariant Generative Framework for Molecular Graph-Structure Co-Design. - Zaixi Zhang; Qi Liu 003; Chee-Kong Lee; Chang-Yu Hsieh; Enhong Chen (CoRR, 2023)

TensorCircuit: a Quantum Software Framework for the NISQ Era. - Shi-Xin Zhang; Jonathan Allcock; Zhou-Quan Wan; Shuo Liu; Jiace Sun; Hao Yu; Xing-Han Yang; Jiezhong Qiu; Zhaofeng Ye; Yu-Qin Chen; Chee-Kong Lee; Yicong Zheng; et al. (Quantum, 2023)

Model Inversion Attacks Against Graph Neural Networks. - Zaixi Zhang; Qi Liu 003; Zhenya Huang; Hao Wang 076; Chee-Kong Lee; Enhong Chen (IEEE Trans. Knowl. Data Eng., 2023)