| Simgnn: A neural network approach to fast graph similarity computation Y Bai, H Ding, S Bian, T Chen, Y Sun, W Wang Proceedings of the twelfth ACM international conference on web search and …, 2019 | 380 | 2019 |
| Unsupervised inductive graph-level representation learning via graph-graph proximity Y Bai, H Ding, Y Qiao, A Marinovic, K Gu, T Chen, Y Sun, W Wang arXiv preprint arXiv:1904.01098, 2019 | 99 | 2019 |
| Learning-based efficient graph similarity computation via multi-scale convolutional set matching Y Bai, H Ding, K Gu, Y Sun, W Wang Proceedings of the AAAI conference on artificial intelligence 34 (04), 3219-3226, 2020 | 98 | 2020 |
| Convolutional set matching for graph similarity Y Bai, H Ding, Y Sun, W Wang arXiv preprint arXiv:1810.10866, 2018 | 51 | 2018 |
| Glsearch: Maximum common subgraph detection via learning to search Y Bai, D Xu, Y Sun, W Wang International Conference on Machine Learning, 588-598, 2021 | 40 | 2021 |
| GHashing: Semantic graph hashing for approximate similarity search in graph databases Z Qin, Y Bai, Y Sun Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 34 | 2020 |
| Automated accelerator optimization aided by graph neural networks A Sohrabizadeh, Y Bai, Y Sun, J Cong Proceedings of the 59th ACM/IEEE Design Automation Conference, 55-60, 2022 | 30 | 2022 |
| Code recommendation for open source software developers Y Jin, Y Bai, Y Zhu, Y Sun, W Wang Proceedings of the ACM Web Conference 2023, 1324-1333, 2023 | 18 | 2023 |
| Dual-geometric space embedding model for two-view knowledge graphs RG Iyer, Y Bai, W Wang, Y Sun Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 18 | 2022 |
| Bi-level graph neural networks for drug-drug interaction prediction Y Bai, K Gu, Y Sun, W Wang arXiv preprint arXiv:2006.14002, 2020 | 17 | 2020 |
| Fast detection of maximum common subgraph via deep q-learning Y Bai, D Xu, A Wang, K Gu, X Wu, A Marinovic, C Ro, Y Sun, W Wang arXiv preprint arXiv:2002.03129 16, 1235-1243, 2020 | 16 | 2020 |
| Hierarchical and Fast Graph Similarity Computation via Graph Coarsening and Deep Graph Learning H Xu, R Chen, Y Bai, J Feng, Z Duan, K Luo, Y Sun, W Wang arXiv preprint arXiv:2005.07115, 2020 | 12 | 2020 |
| Graph edit distance computation via graph neural networks Y Bai, H Ding, S Bian, T Chen, Y Sun, W Wang arXiv preprint arXiv:1808.05689, 2018 | 12 | 2018 |
| Robust GNN-based representation learning for HLS A Sohrabizadeh, Y Bai, Y Sun, J Cong 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 1-9, 2023 | 10 | 2023 |
| Improving GNN-based accelerator design automation with meta learning Y Bai, A Sohrabizadeh, Y Sun, J Cong Proceedings of the 59th ACM/IEEE Design Automation Conference, 1347-1350, 2022 | 10 | 2022 |
| Unsupervised inductive whole-graph embedding by preserving graph proximity Y Bai, H Ding, Y Qiao, A Marinovic, K Gu, T Chen, Y Sun, W Wang Proceedings of the seventh international conference on learning …, 2019 | 10 | 2019 |
| Enabling automated FPGA accelerator optimization using graph neural networks A Sohrabizadeh, Y Bai, Y Sun, J Cong arXiv preprint arXiv:2111.08848, 2021 | 9 | 2021 |
| Neural maximum common subgraph detection with guided subgraph extraction Y Bai, D Xu, K Gu, X Wu, A Marinovic, C Ro, Y Sun, W Wang | 7 | 2020 |
| Towards a comprehensive benchmark for high-level synthesis targeted to FPGAs Y Bai, A Sohrabizadeh, Z Qin, Z Hu, Y Sun, J Cong Advances in Neural Information Processing Systems 36, 45288-45299, 2023 | 6 | 2023 |
| CoSimGNN: towards large-scale graph similarity computation H Xu, R Chen, Y Wang, Z Duan, J Feng arXiv preprint arXiv:2005.07115, 2020 | 5 | 2020 |
