| KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation X Wang, T Gao, Z Zhu, Z Zhang, Z Liu, J Li, J Tang Transactions of the Association for Computational Linguistics 9, 176-194, 2021 | 626 | 2021 |
| GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation C Shi*, M Xu*, Z Zhu, W Zhang, M Zhang, J Tang International Conference on Learning Representations, 2020 | 422 | 2020 |
| Neural bellman-ford networks: A general graph neural network framework for link prediction Z Zhu, Z Zhang, LP Xhonneux, J Tang Advances in Neural Information Processing Systems 34, 29476-29490, 2021 | 253 | 2021 |
| GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding Z Zhu, S Xu, M Qu, J Tang The World Wide Web Conference, 2494-2504, 2019 | 143 | 2019 |
| TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery Z Zhu, C Shi, Z Zhang, S Liu, M Xu, X Yuan, Y Zhang, J Chen, H Cai, J Lu, ... arXiv preprint arXiv:2202.08320, 2022 | 69 | 2022 |
| Neural-Symbolic Models for Logical Queries on Knowledge Graphs Z Zhu, M Galkin, Z Zhang, J Tang International Conference on Machine Learning, 2022 | 59 | 2022 |
| PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding M Xu*, Z Zhang*, J Lu, Z Zhu, Y Zhang, C Ma, R Liu, J Tang Advances in Neural Information Processing Systems, 2022 | 58 | 2022 |
| Dialog state tracking with attention-based sequence-to-sequence learning T Hori, H Wang, C Hori, S Watanabe, B Harsham, J Le Roux, JR Hershey, ... 2016 IEEE Spoken Language Technology Workshop (SLT), 552-558, 2016 | 40 | 2016 |
| GraphText: Graph Reasoning in Text Space J Zhao, L Zhuo, Y Shen, M Qu, K Liu, M Bronstein, Z Zhu, J Tang arXiv preprint arXiv:2310.01089, 2023 | 32 | 2023 |
| Self-Adaptive Network Pruning J Chen, Z Zhu, C Li, Y Zhao International Conference on Neural Information Processing, 175-186, 2019 | 25 | 2019 |
| Large Language Models can Learn Rules Z Zhu, Y Xue, X Chen, D Zhou, J Tang, D Schuurmans, H Dai arXiv preprint arXiv:2310.07064, 2023 | 24 | 2023 |
| Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases H Ren, M Galkin, M Cochez, Z Zhu, J Leskovec arXiv preprint arXiv:2303.14617, 2023 | 23 | 2023 |
| Inductive logical query answering in knowledge graphs M Galkin, Z Zhu, H Ren, J Tang Advances in Neural Information Processing Systems 35, 15230-15243, 2022 | 22 | 2022 |
| Towards Foundation Models for Knowledge Graph Reasoning M Galkin, X Yuan, H Mostafa, J Tang, Z Zhu arXiv preprint arXiv:2310.04562, 2023 | 21 | 2023 |
| A* net: A scalable path-based reasoning approach for knowledge graphs Z Zhu*, X Yuan*, M Galkin, LP Xhonneux, M Zhang, M Gazeau, J Tang Advances in Neural Information Processing Systems 36, 2023 | 19* | 2023 |
| Context Aware Document Embedding Z Zhu, J Hu arXiv preprint arXiv:1707.01521, 2017 | 19 | 2017 |
| Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets D Beaini, S Huang, JA Cunha, G Moisescu-Pareja, O Dymov, ... arXiv preprint arXiv:2310.04292, 2023 | 11 | 2023 |
| Zero-shot Logical Query Reasoning on any Knowledge Graph M Galkin, J Zhou, B Ribeiro, J Tang, Z Zhu arXiv preprint arXiv:2404.07198, 2024 | 2 | 2024 |
| Saliency Supervision: An intuitive and effective approach for pain intensity regression C Li, Z Zhu, Y Zhao Neural Information Processing: 25th International Conference, ICONIP 2018 …, 2018 | 1 | 2018 |
| GraphAny: A Foundation Model for Node Classification on Any Graph J Zhao, H Mostafa, M Galkin, M Bronstein, Z Zhu, J Tang arXiv preprint arXiv:2405.20445, 2024 | | 2024 |
Jian Tang (唐建）Associate Professor, Mila-Quebec AI Institute, HEC Montréal, Canada CIFAR AI Chair在 hec.ca 的电子邮件经过验证
