| Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning J Cheng, M Li, J Li, F Tsung Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7131-7139, 2023 | 9 | 2023 |
| Handling missing data via max-entropy regularized graph autoencoder Z Gao, Y Niu, J Cheng, J Tang, L Li, T Xu, P Zhao, F Tsung, J Li Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7651-7659, 2023 | 9 | 2023 |
| Improving generalization in equivariant graph neural networks with physical inductive biases Y Liu, J Cheng, H Zhao, T Xu, P Zhao, F Tsung, J Li, Y Rong The Twelfth International Conference on Learning Representations, 2023 | 3* | 2023 |
| Deep Insights into Noisy Pseudo Labeling on Graph Data W Botao, J Li, Y Liu, J Cheng, Y Rong, W Wang, F Tsung Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 2 | 2023 |
| Latent Augmentation Improves Graph Self-Supervised Learning J Cheng, M Li, J Li, F Tsung arXiv preprint arXiv:2206.12933, 2022 | | 2022 |
