Pooling architecture search for graph classification L Wei, H Zhao, Q Yao, Z He Proceedings of the 30th ACM International Conference on Information …, 2021 | 68 | 2021 |
Simplifying architecture search for graph neural network H Zhao, L Wei, Q Yao arXiv preprint arXiv:2008.11652, 2020 | 58 | 2020 |
Designing the topology of graph neural networks: A novel feature fusion perspective L Wei, H Zhao, Z He Proceedings of the ACM Web Conference 2022, 1381-1391, 2022 | 50 | 2022 |
Neural architecture search for GNN-based graph classification L Wei, H Zhao, Z He, Q Yao ACM Transactions on Information Systems 42 (1), 1-29, 2023 | 17 | 2023 |
Search to Capture Long-range Dependency with Stacking GNNs for Graph Classification L Wei, Z He, H Zhao, Q Yao Proceedings of the ACM Web Conference 2023, 588-598, 2023 | 13 | 2023 |
Unleashing the power of graph learning through llm-based autonomous agents L Wei, Z He, H Zhao, Q Yao arXiv preprint arXiv:2309.04565, 2023 | 7 | 2023 |
Graph Property Prediction on Open Graph Benchmark: A Winning Solution by Graph Neural Architecture Search X Wang, H Zhao, L Wei, Q Yao DLG-KDD 2022, 2022 | 4 | 2022 |
Automated Machine Learning: From Principles to Practices Z Shen, Y Zhang, L Wei, H Zhao, Q Yao arXiv preprint arXiv:1810.13306, 2018 | 4 | 2018 |
Enhancing intra-class information extraction for heterophilous graphs: One neural architecture search approach L Wei, Z He, H Zhao, Q Yao arXiv preprint arXiv:2211.10990, 2022 | 2 | 2022 |
Efficient graph neural architecture search H Zhao, L Wei, Z He | 2 | 2021 |
Heuristic Learning with Graph Neural Networks: A Unified Framework for Link Prediction J Zhang, L Wei, Z Xu, Q Yao Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 1 | 2024 |
Searching Heterophily-Agnostic Graph Neural Networks L Wei, Z He, H Zhao, Q Yao Available at SSRN 4825405, 0 | 1 | |
Towards Versatile Graph Learning Approach: from the Perspective of Large Language Models L Wei, J Gao, H Zhao, Q Yao arXiv preprint arXiv:2402.11641, 2024 | | 2024 |
Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020 Z Xu, L Wei, H Zhao, R Ying, Q Yao, WW Tu, I Guyon Frontiers in Artificial Intelligence 5, 905104, 2022 | | 2022 |