Követés
Jia Li
Jia Li
HKUST Guangzhou
E-mail megerősítve itt: ust.hk - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Semi-supervised graph classification: A hierarchical graph perspective
J Li, Y Rong, H Cheng, H Meng, W Huang, J Huang
The World Wide Web Conference, 972-982, 2019
1412019
Rethinking Graph Neural Networks for Anomaly Detection
J Tang, J Li, Z Gao, J Li
ICML, 2022
1312022
Predicting path failure in time-evolving graphs
J Li, Z Han, H Cheng, J Su, P Wang, J Zhang, L Pan
Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019
1252019
Adversarial attack on community detection by hiding individuals
J Li, H Zhang, Z Han, Y Rong, H Cheng, J Huang
Proceedings of The Web Conference 2020, 917-927, 2020
862020
All in One: Multi-Task Prompting for Graph Neural Networks
X Sun, H Cheng, J Li, B Liu, J Guan
KDD 2023, 2023
66*2023
Hierarchical graph learning for protein–protein interaction
Z Gao, C Jiang, J Zhang, X Jiang, L Li, P Zhao, H Yang, Y Huang, J Li
Nature Communications 14 (1), 1093, 2023
572023
TATC: predicting Alzheimer's disease with actigraphy data
J Li, Y Rong, H Meng, Z Lu, T Kwok, H Cheng
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
512018
Dirichlet graph variational autoencoder
J Li, J Yu, J Li, H Zhang, K Zhao, Y Rong, H Cheng, J Huang
NeurIPS 33, 5274--5283, 2020
452020
Large Language Models Meet Harry Potter: A Bilingual Dataset for Aligning Dialogue Agents with Characters
N Chen, Y Wang, H Jiang, D Cai, Y Li, Z Chen, L Wang, J Li
EMNLP Findings, 2023
28*2023
Deconvolutional Networks on Graph Data
J Li, J Li, Y Liu, J Yu, Y Li, H Cheng
NeurIPS 34, 21019--21030, 2021
232021
A survey of graph meets large language model: Progress and future directions
Y Li, Z Li, P Wang, J Li, X Sun, H Cheng, JX Yu
IJCAI 2024, 2023
222023
Self-supervised hypergraph representation learning for sociological analysis
X Sun, H Cheng, B Liu, J Li, H Chen, G Xu, H Yin
IEEE Transactions on Knowledge and Data Engineering, 2023
222023
Semi-supervised hierarchical graph classification
J Li, Y Huang, H Chang, Y Rong
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (5), 6265-6276, 2022
182022
Graph prompt learning: A comprehensive survey and beyond
X Sun, J Zhang, X Wu, H Cheng, Y Xiong, J Li
arXiv preprint arXiv:2311.16534, 2023
172023
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
J Tang, F Hua, Z Gao, P Zhao, J Li
NeurIPS 2023, 2023
172023
Breaking language barriers in multilingual mathematical reasoning: Insights and observations
N Chen, Z Zheng, N Wu, L Shou, M Gong, Y Song, D Zhang, J Li
arXiv preprint arXiv:2310.20246, 2023
152023
A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data
J Li, J Tang, L Kong, H Liu, J Li, AMC So, J Blanchet
ICLR 2023, 2023
14*2023
Wiener Graph Deconvolutional Network Improves Graph Self-Supervised Learning
J Cheng, M Li, J Li, F Tsung
AAAI 2023, 2023
132023
Handling Missing Data via Max-Entropy Regularized Graph Autoencoder
Z Gao, Y Niu, J Cheng, J Tang, T Xu, P Zhao, L Li, F Tsung, J Li
AAAI 2023, 2022
122022
Alleviating Over-smoothing for Unsupervised Sentence Representation
N Chen, L Shou, M Gong, J Pei, B Cao, J Chang, D Jiang, J Li
ACL 2023, 2023
102023
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Cikkek 1–20