The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud Detection. - Zhixun Li; Dingshuo Chen; Qiang Liu 006; Shu Wu (ICDM, 2022)

Improving Molecular Pretraining with Complementary Featurizations. - Yanqiao Zhu 001; Dingshuo Chen; Yuanqi Du; Yingze Wang; Qiang Liu 006; Shu Wu (CoRR, 2022)

Learning Graph Structures With Transformer for Multivariate Time-Series Anomaly Detection in IoT. - Zekai Chen; Dingshuo Chen; Xiao Zhang 015; Zixuan Yuan; Xiuzhen Cheng 001 (IEEE Internet Things J., 2022)

Uncovering Neural Scaling Laws in Molecular Representation Learning. - Dingshuo Chen; Yanqiao Zhu 001; Jieyu Zhang 001; Yuanqi Du; Zhixun Li; Qiang Liu 006; Shu Wu; Liang Wang 056 (NeurIPS, 2023)

GSLB: The Graph Structure Learning Benchmark. - Zhixun Li; Xin Sun; Yifan Luo; Yanqiao Zhu 001; Dingshuo Chen; Yingtao Luo; Xiangxin Zhou; Qiang Liu 006; Shu Wu; Liang Wang 001; Jeffrey Xu Yu (NeurIPS, 2023)

Uncovering Neural Scaling Laws in Molecular Representation Learning. - Dingshuo Chen; Yanqiao Zhu 001; Jieyu Zhang 001; Yuanqi Du; Zhixun Li; Qiang Liu 006; Shu Wu; Liang Wang 001 (CoRR, 2023)

GSLB: The Graph Structure Learning Benchmark. - Zhixun Li; Liang Wang 056; Xin Sun; Yifan Luo; Yanqiao Zhu 001; Dingshuo Chen; Yingtao Luo; Xiangxin Zhou; Qiang Liu 006; Shu Wu; Liang Wang 001; Jeffrey Xu Yu (CoRR, 2023)

Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization. - Dingshuo Chen; Zhixun Li; Yuyan Ni; Guibin Zhang; Ding Wang; Qiang Liu 006; Shu Wu; Jeffrey Xu Yu; Liang Wang (NeurIPS, 2024)

GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning. - Guibin Zhang; Haonan Dong; Yuchen Zhang; Zhixun Li; Dingshuo Chen; Kai Wang 036; Tianlong Chen 001; Yuxuan Liang; Dawei Cheng; Kun Wang 056 (NeurIPS, 2024)

GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning. - Guibin Zhang; Haonan Dong; Yuchen Zhang; Zhixun Li; Dingshuo Chen; Kai Wang 036; Tianlong Chen 001; Yuxuan Liang; Dawei Cheng; Kun Wang 042 (CoRR, 2024)

Molecular Contrastive Pretraining with Collaborative Featurizations. - Yanqiao Zhu 001; Dingshuo Chen; Yuanqi Du; Yingze Wang; Qiang Liu 006; Shu Wu (J. Chem. Inf. Model., 2024)

IceBerg: Debiased Self-Training for Class-Imbalanced Node Classification. - Zhixun Li; Dingshuo Chen; Tong Zhao; Daixin Wang; Hongrui Liu; Zhiqiang Zhang 012; Jun Zhou 011; Jeffrey Xu Yu (WWW, 2025)

Improving Multi-task GNNs for Molecular Property Prediction via Missing Label Imputation. - Fenyu Hu; Dingshuo Chen; Qiang Liu 006; Shu Wu (Mach. Intell. Res., 2025)

Graffe: Graph Representation Learning via Diffusion Probabilistic Models. - Dingshuo Chen; Shuchen Xue; Liuji Chen; Yingheng Wang; Qiang Liu; Shu Wu; Zhi-Ming Ma; Liang Wang (CoRR, 2025)

Materials Generation in the Era of Artificial Intelligence: A Comprehensive Survey. - Zhixun Li; Bin Cao; Rui Jiao; Liang Wang 056; Ding Wang; Yang Liu 003; Dingshuo Chen; Jia Li 009; Qiang Liu 006; Yu Rong 001; Liang Wang 001; Tong-yi Zhang; et al. (CoRR, 2025)