Dingshuo Chen

According to our database, Dingshuo Chen authored at least 15 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Materials Generation in the Era of Artificial Intelligence: A Comprehensive Survey.

Zhixun Li, Bin Cao, Rui Jiao, Liang Wang, Ding Wang, Yang Liu, Dingshuo Chen, Jia Li, Qiang Liu, Yu Rong, Liang Wang, Tong-yi Zhang, Jeffrey Xu Yu

CoRR, May, 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, May, 2025

Improving Multi-task GNNs for Molecular Property Prediction via Missing Label Imputation.

Fenyu Hu, Dingshuo Chen, Qiang Liu, Shu Wu

Mach. Intell. Res., February, 2025

IceBerg: Debiased Self-Training for Class-Imbalanced Node Classification.

Zhixun Li, Dingshuo Chen, Tong Zhao, Daixin Wang, Hongrui Liu, Zhiqiang Zhang, Jun Zhou, Jeffrey Xu Yu

Proceedings of the ACM on Web Conference 2025, 2025

2024

Molecular Contrastive Pretraining with Collaborative Featurizations.

Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu

J. Chem. Inf. Model., February, 2024

GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning.

Guibin Zhang, Haonan Dong, Yuchen Zhang, Zhixun Li, Dingshuo Chen, Kai Wang, Tianlong Chen, Yuxuan Liang, Dawei Cheng, Kun Wang

CoRR, 2024

GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning.

Guibin Zhang, Haonan Dong, Yuchen Zhang, Zhixun Li, Dingshuo Chen, Kai Wang, Tianlong Chen, Yuxuan Liang, Dawei Cheng, Kun Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization.

Dingshuo Chen, Zhixun Li, Yuyan Ni, Guibin Zhang, Ding Wang, Qiang Liu, Shu Wu, Jeffrey Xu Yu, Liang Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

GSLB: The Graph Structure Learning Benchmark.

Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu

CoRR, 2023

Uncovering Neural Scaling Laws in Molecular Representation Learning.

Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang

CoRR, 2023

GSLB: The Graph Structure Learning Benchmark.

Zhixun Li, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Uncovering Neural Scaling Laws in Molecular Representation Learning.

Dingshuo Chen, Yanqiao Zhu, Jieyu Zhang, Yuanqi Du, Zhixun Li, Qiang Liu, Shu Wu, Liang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Learning Graph Structures With Transformer for Multivariate Time-Series Anomaly Detection in IoT.

Zekai Chen, Dingshuo Chen, Xiao Zhang, Zixuan Yuan, Xiuzhen Cheng

IEEE Internet Things J., 2022

Improving Molecular Pretraining with Complementary Featurizations.

Yanqiao Zhu, Dingshuo Chen, Yuanqi Du, Yingze Wang, Qiang Liu, Shu Wu

CoRR, 2022

The Devil is in the Conflict: Disentangled Information Graph Neural Networks for Fraud Detection.

Zhixun Li, Dingshuo Chen, Qiang Liu, Shu Wu

Proceedings of the IEEE International Conference on Data Mining, 2022