| Learning from counterfactual links for link prediction T Zhao, G Liu, D Wang, W Yu, M Jiang International Conference on Machine Learning, 26911-26926, 2022 | 71 | 2022 |
| Error-bounded graph anomaly loss for gnns T Zhao, C Deng, K Yu, T Jiang, D Wang, M Jiang Proceedings of the 29th ACM International Conference on Information …, 2020 | 56 | 2020 |
| Tcn: Table convolutional network for web table interpretation D Wang, P Shiralkar, C Lockard, B Huang, XL Dong, M Jiang Proceedings of the Web Conference 2021, 4020-4032, 2021 | 52 | 2021 |
| Calendar graph neural networks for modeling time structures in spatiotemporal user behaviors D Wang, M Jiang, M Syed, O Conway, V Juneja, S Subramanian, ... Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 46 | 2020 |
| Multi-type itemset embedding for learning behavior success D Wang, M Jiang, Q Zeng, Z Eberhart, NV Chawla Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 32 | 2018 |
| Counterfactual graph learning for link prediction T Zhao, G Liu, D Wang, W Yu, M Jiang | 16 | 2021 |
| Modeling co-evolution of attributed and structural information in graph sequence D Wang, Z Zhang, Y Ma, T Zhao, T Jiang, NV Chawla, M Jiang IEEE Transactions on Knowledge and Data Engineering 35 (2), 1817-1830, 2021 | 14 | 2021 |
| Tube: Embedding behavior outcomes for predicting success D Wang, T Jiang, NV Chawla, M Jiang Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 12 | 2019 |
| Learning attribute-structure co-evolutions in dynamic graphs D Wang, Z Zhang, Y Ma, T Zhao, T Jiang, NV Chawla, M Jiang arXiv preprint arXiv:2007.13004, 2020 | 9 | 2020 |
| Deep multimodal complementarity learning D Wang, T Zhao, W Yu, NV Chawla, M Jiang IEEE Transactions on Neural Networks and Learning Systems, 2022 | 8 | 2022 |
| Gnn-based graph anomaly detection with graph anomaly loss T Zhao, C Deng, K Yu, T Jiang, D Wang, M Jiang The Second International Workshop on Deep Learning on Graphs: Methods and …, 2020 | 8 | 2020 |
| Dynamic attributed graph prediction with conditional normalizing flows D Wang, T Zhao, NV Chawla, M Jiang 2021 IEEE International Conference on Data Mining (ICDM), 1385-1390, 2021 | 7 | 2021 |
| Modeling complementarity in behavior data with multi-type itemset embedding D Wang, Q Zeng, NV Chawla, M Jiang ACM Transactions on Intelligent Systems and Technology (TIST) 12 (4), 1-25, 2021 | 4 | 2021 |
| Unified representation of twitter and online news using graph and entities M Syed, D Wang, M Jiang, O Conway, V Juneja, S Subramanian, ... Frontiers in big Data 4, 699070, 2021 | 2 | 2021 |
| Multifaceted Event Analysis on Cross-Media Network Data D Wang, M Jiang, X Wang, N Chawla, P Brunts Proceedings of the 1st International Workshop on Heterogeneous Networks …, 2018 | 2 | 2018 |
| Preserving Composition and Crystal Structures of Chemical Compounds in Atomic Embedding Y Ding, D Wang, T Weninger, M Jiang 2019 IEEE International Conference on Big Data (Big Data), 6037-6039, 2019 | 1 | 2019 |
| A project showcase for planning research work towards publishable success D Wang, M Jiang, X Wang, T Zhao, Q Zeng, NV Chawla KDD, 2018 | 1 | 2018 |
| Evolutionary Graph Normalizing Flows D Wang, T Zhao, NV Chawla, M Jiang | | 2021 |
| Learning Complementarity and Dynamics for Contextual Behavior Modeling D Wang University of Notre Dame, 2021 | | 2021 |
| Overcoming data sparsity in predicting user characteristics from behavior through graph embeddings M Syed, D Wang, M Jiang, O Conway, V Juneja, S Subramanian, ... 2020 IEEE/ACM International Conference on Advances in Social Networks …, 2020 | | 2020 |
Meng JiangUniversity of Notre DameVerified email at nd.edu
