| 2025 | AAAI | GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation. | Shengyin Sun, Wenhao Yu, Yuxiang Ren, Weitao Du, Liwei Liu, Xuecang Zhang, Ying Hu, Chen Ma |
| 2024 | DASFAA | CGCL: Collaborative Graph Contrastive Learning Without Handcrafted Graph Data Augmentations. | Tianyu Zhang, Yuxiang Ren, Wenzheng Feng, Weitao Du, Xuecang Zhang |
| 2023 | ICML | A Flexible Diffusion Model. | Weitao Du, He Zhang, Tao Yang, Yuanqi Du |
| 2023 | ICML | A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining. | Shengchao Liu, Weitao Du, Zhi-Ming Ma, Hongyu Guo, Jian Tang |
| 2022 | ICLR | Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective. | Wei Huang, Yayong Li, Weitao Du, Richard Y. D. Xu, Jie Yin, Ling Chen, Miao Zhang |
| 2022 | ICML | SE(3) Equivariant Graph Neural Networks with Complete Local Frames. | Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu |
| 2021 | IJCAI | On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization. | Wei Huang, Weitao Du, Richard Yi Da Xu |
| 2020 | ECAI | Mean Field Theory for Deep Dropout Networks: Digging up Gradient Backpropagation Deeply. | Wei Huang, Richard Yi Da Xu, Weitao Du, Yutian Zeng, Yunce Zhao |