A comprehensive survey on deep graph representation learning W Ju, Z Fang, Y Gu, Z Liu, Q Long, Z Qiao, Y Qin, J Shen, F Sun, Z Xiao, ...
Neural Networks, 106207, 2024
151 2024 A deep‐learning model using automated performance metrics and clinical features to predict urinary continence recovery after robot‐assisted radical prostatectomy AJ Hung, J Chen, S Ghodoussipour, PJ Oh, Z Liu, J Nguyen, ...
BJU international 124 (3), 487-495, 2019
133 2019 Molxpt: Wrapping molecules with text for generative pre-training Z Liu, W Zhang, Y Xia, L Wu, S Xie, T Qin, M Zhang, TY Liu
ACL 2023, 2023
75 2023 Few-shot molecular property prediction via hierarchically structured learning on relation graphs W Ju, Z Liu, Y Qin, B Feng, C Wang, Z Guo, X Luo, M Zhang
Neural Networks 163, 122-131, 2023
54 2023 Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks Y Song, Z Liu, W Bi, R Yan, M Zhang
ACL 2020, 2019
44 * 2019 Multi-task learning via adaptation to similar tasks for mortality prediction of diverse rare diseases L Liu, Z Liu, H Wu, Z Wang, J Shen, Y Song, M Zhang
Amia annual symposium proceedings 2020, 763, 2021
27 2021 Poisoning medical knowledge using large language models J Yang, H Xu, S Mirzoyan, T Chen, Z Liu, Z Liu, W Ju, L Liu, Z Xiao, ...
Nature Machine Intelligence 6 (10), 1156-1168, 2024
25 * 2024 When does maml work the best? an empirical study on model-agnostic meta-learning in nlp applications Z Liu, R Zhang, Y Song, W Ju, M Zhang
arXiv preprint arXiv:2005.11700, 2020
15 2020 Graphine: A dataset for graph-aware terminology definition generation Z Liu, S Wang, Y Gu, R Zhang, M Zhang, S Wang
EMNLP 2021, 2021
13 2021 A bioactivity foundation model using pairwise meta-learning B Feng, Z Liu, N Huang, Z Xiao, H Zhang, S Mirzoyan, H Xu, J Hao, Y Xu, ...
Nature Machine Intelligence 6 (8), 962-974, 2024
11 2024 Early prediction of sepsis from clinical data via heterogeneous event aggregation L Liu, H Wu, Z Wang, Z Liu, M Zhang
2019 Computing in Cardiology (CinC), Page 1-Page 4, 2019
11 2019 Pathway2text: Dataset and method for biomedical pathway description generation J Yang, Z Liu, M Zhang, S Wang
Findings of the Association for Computational Linguistics: NAACL 2022, 1441-1454, 2022
3 2022 SMI-Editor: Edit-based SMILES Language Model with Fragment-level Supervision K Zheng, S Liang, J Yang, B Feng, Z Liu, W Ju, Z Xiao, M Zhang
ICLR 2025, 2024
1 2024 Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data B Feng, T Ao, Z Liu, W Ju, L Liu, M Zhang
arXiv preprint arXiv:2303.16856, 2023
1 2023 MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information Networks Z Liu, K Duan, J Yang, H Xu, M Zhang, S Wang
EMNLP 2022, 2022
1 2022 PD27-07 DEEP LEARNING MODEL TO PREDICT TIME TO URINARY CONTINENCE RECOVERY AFTER ROBOT-ASSISTED RADICAL PROSTATECTOMY USING AUTOMATED PERFORMANCE METRICS AND CLINICAL DATA A Hung, J Chen, Z Liu, J Nguyen, P Oh, D Stewart, D Remulla, T Chu, ...
Journal of Urology 201, e483, 2019
1 2019 NatureLM: Deciphering the Language of Nature for Scientific Discovery Y Xia, P Jin, S Xie, L He, C Cao, R Luo, G Liu, Y Wang, Z Liu, YJ Chen, ...
arXiv preprint arXiv:2502.07527, 2025
2025 ExLM: Rethinking the Impact of K Zheng, J Yang, S Liang, B Feng, Z Liu, W Ju, Z Xiao, M Zhang
arXiv preprint arXiv:2501.13397, 2025
2025 MP60-14 COMPARING DEEP LEARNING, MACHINE LEARNING, AND CONVENTIONAL REGRESSION AS PREDICTIVE MODELS OF TIME TO URINARY CONTINENCE AFTER ROBOT-ASSISTED RADICAL PROSTATECTOMY A Hung, J Chen, Z Liu, J Nguyen, S Purushotham, Y Liu
Journal of Urology 201, e874, 2019
2019 Deep learning model to predict urinary continence after robot-assisted radical prostatectomy A Hung, J Chen, ZQ Liu, J Nguyen, S Purushotham, Y Liu
European Urology Supplements 18 (1), e851, 2019
2019 
Ming Zhang（张铭）Professor,Peking UniversityПотвърден имейл адрес: pku.edu.cn