| One for all: Towards training one graph model for all classification tasks H Liu, J Feng, L Kong, N Liang, D Tao, Y Chen, M Zhang arXiv preprint arXiv:2310.00149, 2023 | 94* | 2023 |
| Geodesic Graph Neural Network for Efficient Graph Representation Learning L Kong, Y Chen, M Zhang Advances in Neural Information Processing Systems 35, 5896--5909, 2022 | 29 | 2022 |
| Extending the design space of graph neural networks by rethinking folklore Weisfeiler-Lehman J Feng, L Kong, H Liu, D Tao, F Li, M Zhang, Y Chen Advances in Neural Information Processing Systems 36, 2024 | 15* | 2024 |
| Mag-gnn: Reinforcement learning boosted graph neural network L Kong, J Feng, H Liu, D Tao, Y Chen, M Zhang Advances in Neural Information Processing Systems 36, 2024 | 15 | 2024 |
| Manipulating elections by changing voter perceptions J Wu, A Estornell, L Kong, Y Vorobeychik arXiv preprint arXiv:2205.00102, 2022 | 7 | 2022 |
| Gofa: A generative one-for-all model for joint graph language modeling L Kong, J Feng, H Liu, C Huang, J Huang, Y Chen, M Zhang arXiv preprint arXiv:2407.09709, 2024 | 5 | 2024 |
| Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks H Liu, J Feng, L Kong, D Tao, Y Chen, M Zhang Proceedings of the ACM on Web Conference 2024, 365-376, 2024 | 2 | 2024 |
| A multi-view joint learning framework for embedding clinical codes and text using graph neural networks L Kong, C King, B Fritz, Y Chen arXiv preprint arXiv:2301.11608, 2023 | 2 | 2023 |
| TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models J Feng, H Liu, L Kong, M Zhu, Y Chen, M Zhang arXiv preprint arXiv:2406.14683, 2024 | | 2024 |
| Time Associated Meta Learning for Clinical Prediction H Liu, M Zhang, Z Dong, L Kong, Y Chen, B Fritz, D Tao, C King arXiv preprint arXiv:2303.02570, 2023 | | 2023 |
Yixin ChenProfessor of Computer Science, Washington UniversityAdresse e-mail validée de cse.wustl.edu
