Segui
Zequn Liu
Zequn Liu
Email verificata su pku.edu.cn
Titolo
Citata da
Citata da
Anno
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
1142019
Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks
Y Song, Z Liu, W Bi, R Yan, M Zhang
ACL 2020, 2019
41*2019
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
36*2024
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
arXiv preprint arXiv:2305.10688, 2023
312023
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, 2020
232020
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
192023
When does maml work the best? an empirical study on model-agnostic meta-learning in nlp applications
Z Liu, R Zhang, Y Song, M Zhang
arXiv preprint arXiv:2005.11700, 2020
142020
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
102019
Graphine: A dataset for graph-aware terminology definition generation
Z Liu, S Wang, Y Gu, R Zhang, M Zhang, S Wang
EMNLP 2021, 2021
92021
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
22022
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, ...
The Journal of Urology 201 (Supplement 4), e483-e483, 2019
12019
A foundation model for bioactivity prediction using pairwise meta-learning
B Feng, Z Liu, N Huang, Z Xiao, H Zhang, S Mirzoyan, H Xu, J Hao, Y Xu, ...
bioRxiv, 2023.10. 30.564861, 2023
2023
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
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
2022
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
The Journal of Urology 201 (Supplement 4), e874-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
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–16