| Explainability in graph neural networks: A taxonomic survey H Yuan, H Yu, S Gui, S Ji IEEE transactions on pattern analysis and machine intelligence 45 (5), 5782-5799, 2022 | 771 | 2022 |
| On explainability of graph neural networks via subgraph explorations H Yuan, H Yu, J Wang, K Li, S Ji International conference on machine learning, 12241-12252, 2021 | 451 | 2021 |
| Xgnn: Towards model-level explanations of graph neural networks H Yuan, J Tang, X Hu, S Ji Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 440 | 2020 |
| Structpool: Structured graph pooling via conditional random fields H Yuan, S Ji Proceedings of the 8th international conference on learning representations, 2020 | 215 | 2020 |
| Pixel transposed convolutional networks H Gao, H Yuan, Z Wang, S Ji IEEE transactions on pattern analysis and machine intelligence 42 (5), 1218-1227, 2019 | 199* | 2019 |
| Xfake: Explainable fake news detector with visualizations F Yang, SK Pentyala, S Mohseni, M Du, H Yuan, R Linder, ED Ragan, S Ji, ... The world wide web conference, 3600-3604, 2019 | 157 | 2019 |
| DIG: A turnkey library for diving into graph deep learning research M Liu, Y Luo, L Wang, Y Xie, H Yuan, S Gui, H Yu, Z Xu, J Zhang, Y Liu, ... Journal of Machine Learning Research 22 (240), 1-9, 2021 | 105 | 2021 |
| Deep learning of high-order interactions for protein interface prediction Y Liu, H Yuan, L Cai, S Ji Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 71 | 2020 |
| Interpreting deep models for text analysis via optimization and regularization methods H Yuan, Y Chen, X Hu, S Ji Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5717-5724, 2019 | 48 | 2019 |
| Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora M Oztekin, Xuan Zhang, and Shuiwang Ji. DIG: A turnkey library for diving into … M Liu, Y Luo, L Wang, Y Xie, H Yuan Journal of Machine Learning Research 22 (240), 1-9, 2021 | 46 | 2021 |
| Global pixel transformers for virtual staining of microscopy images Y Liu, H Yuan, Z Wang, S Ji IEEE Transactions on Medical Imaging 39 (6), 2256-2266, 2020 | 44 | 2020 |
| Interpreting image classifiers by generating discrete masks H Yuan, L Cai, X Hu, J Wang, S Ji IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (4), 2019-2030, 2020 | 34 | 2020 |
| Computational modeling of cellular structures using conditional deep generative networks H Yuan, L Cai, Z Wang, X Hu, S Zhang, S Ji Bioinformatics 35 (12), 2141-2149, 2019 | 31 | 2019 |
| Flowx: Towards explainable graph neural networks via message flows S Gui, H Yuan, J Wang, Q Lao, K Li, S Ji IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 16 | 2023 |
| Towards improved and interpretable deep metric learning via attentive grouping X Xu, Z Wang, C Deng, H Yuan, S Ji IEEE transactions on pattern analysis and machine intelligence 45 (1), 1189-1200, 2022 | 14 | 2022 |
| Fast quantum property prediction via deeper 2d and 3d graph networks M Liu, C Fu, X Zhang, L Wang, Y Xie, H Yuan, Y Luo, Z Xu, S Xu, S Ji arXiv preprint arXiv:2106.08551, 2021 | 13 | 2021 |
| Learning hierarchical and shared features for improving 3D neuron reconstruction H Yuan, N Zou, S Zhang, H Peng, S Ji 2019 IEEE International Conference on Data Mining (ICDM), 806-815, 2019 | 13 | 2019 |
| Learning local and global multi-context representations for document classification Y Liu, H Yuan, S Ji 2019 IEEE International Conference on Data Mining (ICDM), 1234-1239, 2019 | 10 | 2019 |
| Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions Z Wang, H Yuan, S Ji Proceedings of the 2019 SIAM International Conference on Data Mining, 648-656, 2019 | 10 | 2019 |
| Node2seq: Towards trainable convolutions in graph neural networks H Yuan, S Ji arXiv preprint arXiv:2101.01849, 2021 | 7 | 2021 |
Shuiwang Ji, Professor and Truchard...Department of Computer Science & Engineering, Texas A&M UniversityVerified email at tamu.edu
