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Tianwen Jiang
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Error-bounded graph anomaly loss for gnns
T Zhao, C Deng, K Yu, T Jiang, D Wang, M Jiang
Proceedings of the 29th ACM International Conference on Information …, 2020
592020
The Role of "Condition": A Novel Scientific Knowledge Graph Representation and Construction Model
T Jiang, T Zhao, B Qin, T Liu, NV Chawla, M Jiang
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
492019
A synergistic approach for graph anomaly detection with pattern mining and feature learning
T Zhao, T Jiang, N Shah, M Jiang
IEEE Transactions on Neural Networks and Learning Systems 33 (6), 2393-2405, 2021
442021
Biomedical knowledge graphs construction from conditional statements
T Jiang, Q Zeng, T Zhao, B Qin, T Liu, NV Chawla, M Jiang
IEEE/ACM transactions on computational biology and bioinformatics 18 (3 …, 2020
162020
Multi-Input Multi-Output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text
T Jiang, T Zhao, B Qin, T Liu, NV Chawla, M Jiang
2019 Conference on Empirical Methods in Natural Language Processing, 2019
162019
Modeling co-evolution of attributed and structural information in graph sequence
D Wang, Z Zhang, Y Ma, T Zhao, T Jiang, NV Chawla, M Jiang
IEEE Transactions on Knowledge and Data Engineering 35 (2), 1817-1830, 2021
142021
Tube: Embedding behavior outcomes for predicting success
D Wang, T Jiang, NV Chawla, M Jiang
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
122019
Tri-train: Automatic pre-fine tuning between pre-training and fine-tuning for sciner
Q Zeng, W Yu, M Yu, T Jiang, T Weninger, M Jiang
Findings of the Association for Computational Linguistics: EMNLP 2020, 4778-4787, 2020
92020
Learning attribute-structure co-evolutions in dynamic graphs
D Wang, Z Zhang, Y Ma, T Zhao, T Jiang, NV Chawla, M Jiang
arXiv preprint arXiv:2007.13004, 2020
92020
Gnn-based graph anomaly detection with graph anomaly loss
T Zhao, C Deng, K Yu, T Jiang, D Wang, M Jiang
The Second International Workshop on Deep Learning on Graphs: Methods and …, 2020
92020
Validating label consistency in ner data annotation
Q Zeng, M Yu, W Yu, T Jiang, M Jiang
arXiv preprint arXiv:2101.08698, 2021
72021
CTGA: Graph-based Biomedical Literature Search
T Jiang, Z Zhang, T Zhao, B Qin, T Liu, NV Chawla, M Jiang
2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019
52019
Open Domain Knowledge Reasoning for Chinese Based on Representation Learning
T Jiang, B Qin, T Liu
J. Chin. Inf. Process 32, 34-41, 2018
42018
Constructing semantic hierarchies via fusion learning architecture
T Jiang, M Liu, B Qin, T Liu
Information Retrieval: 23rd China conference, CCIR 2017, Shanghai, China …, 2017
42017
VEML: A Plug-and-play Framework for Fusing Text and Structure Knowledge on Sparse Knowledge Graph Completion
T He, M Liu, Y Cao, T Jiang, Z Zheng, J Zhang, S Zhao, B Qin
arXiv preprint arXiv:2207.01528, 2022
32022
Canonicalizing open knowledge bases with multi-layered meta-graph neural network
T Jiang, T Zhao, B Qin, T Liu, NV Chawla, M Jiang
arXiv preprint arXiv:2006.09610, 2020
32020
基于表示学习的开放域中文知识推理
姜天文, 秦兵, 刘挺
中文信息学报 32 (3), 34-41, 2018
32018
Constructing information-lossless biological knowledge graphs from conditional statements
T Jiang, T Zhao, B Qin, T Liu, NV Chawla, M Jiang
arXiv preprint arXiv:1907.00720, 2019
22019
Towards Time-Aware Distant Supervision for Relation Extraction
T Jiang, S Zhao, J Liu, JG Yao, M Liu, B Qin, T Liu, CY Lin
arXiv preprint arXiv:1903.03289, 2019
22019
Use of “Internal Knowledge”: Biomedical Literature Search Liberated From External Resources
T Jiang, N Zhang, M Liu, M Jiang, T Liu, B Qin
2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2020
12020
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