| Neural bellman-ford networks: A general graph neural network framework for link prediction Z Zhu, Z Zhang, LP Xhonneux, J Tang NeurIPS 2021 34, 29476-29490, 2021 | 357 | 2021 |
| Protein representation learning by geometric structure pretraining Z Zhang, M Xu, A Jamasb, V Chenthamarakshan, A Lozano, P Das, ... ICLR 2023, 2022 | 233* | 2022 |
| Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data Y Zhao*, H Cai*, Z Zhang, J Tang, Y Li Nature Communications 12 (1), 5261, 2021 | 144 | 2021 |
| 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 NeurIPS 2022 Datasets and Benchmarks Track, 2022 | 91 | 2022 |
| Neural-Symbolic Models for Logical Queries on Knowledge Graphs Z Zhu, M Galkin, Z Zhang, J Tang ICML 2022 162, 27454--27478, 2022 | 89 | 2022 |
| 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 | 82 | 2022 |
| A Systematic Study of Joint Representation Learning on Protein Sequences and Structures Z Zhang, C Wang*, M Xu*, V Chenthamarakshan, A Lozano, P Das, ... ICLR 2023 Machine Learning for Drug Discovery Workshop, 2023 | 53* | 2023 |
| Structured multi-task learning for molecular property prediction S Liu, M Qu, Z Zhang, H Cai, J Tang AISTATS 2022, 8906-8920, 2022 | 35* | 2022 |
| DiffPack: A Torsional Diffusion Model for Autoregressive Protein Side-Chain Packing Y Zhang*, Z Zhang*, B Zhong, S Misra, J Tang NeurIPS 2023, 2023 | 29 | 2023 |
| Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction Z Zhang*, M Xu*, A Lozano, V Chenthamarakshan, P Das, J Tang NeurIPS 2023 Spotlight, 2023 | 26* | 2023 |
| A roadmap for big model S Yuan, H Zhao, S Zhao, J Leng, Y Liang, X Wang, J Yu, X Lv, Z Shao, ... arXiv preprint arXiv:2203.14101, 2022 | 21 | 2022 |
| Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling J Lu, B Zhong, Z Zhang, J Tang ICLR 2024, 2023 | 17* | 2023 |
| FusionRetro: Molecule Representation Fusion via In-context Reactions for Retrosynthetic Planning S Liu, Z Tu, M Xu, Z Zhang, P Zhao, J Tang, R Ying, L Lin, D Wu ICML 2023, 2023 | 17 | 2023 |
| Power-law graphs have minimal scaling of Kemeny constant for random walks W Xu, Y Sheng, Z Zhang, H Kan, Z Zhang WWW 2020, 46-56, 2020 | 16 | 2020 |
| Biharmonic distance-based performance metric for second-order noisy consensus networks Y Yi, B Yang, Z Zhang, Z Zhang, S Patterson IEEE Transactions on Information Theory 68 (2), 1220-1236, 2021 | 12 | 2021 |
| Effects of Stubbornness on Opinion Dynamics W Xu, L Zhu, J Guan, Z Zhang, Z Zhang CIKM 2022, 2321-2330, 2022 | 9 | 2022 |
| Minimizing Spectral Radius of Non-Backtracking Matrix by Edge Removal Z Zhang, Z Zhang, G Chen CIKM 2021, 2657-2667, 2021 | 9 | 2021 |
| Coherence scaling of noisy second-order scale-free consensus networks W Xu, B Wu, Z Zhang, Z Zhang, H Kan, G Chen IEEE Transactions on Cybernetics 52 (7), 5923-5934, 2021 | 9 | 2021 |
| Nearly Linear Time Algorithm for Mean Hitting Times of Random Walks on a Graph Z Zhang, W Xu, Z Zhang WSDM 2020, 726-734, 2020 | 8 | 2020 |
| Fast approximation of coherence for second-order noisy consensus networks Z Zhang, W Xu, Y Yi, Z Zhang IEEE Transactions on Cybernetics 52 (1), 677-686, 2020 | 7 | 2020 |
Jian Tang (唐建）Associate Professor, Mila-Quebec AI Institute, HEC Montréal, Canada CIFAR AI ChairVerified email at hec.ca
