Di Jin
Di Jin
Verifierad e-postadress på tju.edu.cn - Startsida
Citeras av
Citeras av
Textattack: A framework for adversarial attacks, data augmentation, and adversarial training in nlp
JX Morris, E Lifland, JY Yoo, J Grigsby, D Jin, Y Qi
arXiv preprint arXiv:2005.05909, 2020
A comprehensive survey on graph anomaly detection with deep learning
X Ma, J Wu, S Xue, J Yang, C Zhou, QZ Sheng, H Xiong, L Akoglu
IEEE Transactions on Knowledge and Data Engineering 35 (12), 12012-12038, 2021
A comprehensive survey on community detection with deep learning
X Su, S Xue, F Liu, J Wu, J Yang, C Zhou, W Hu, C Paris, S Nepal, D Jin, ...
IEEE Transactions on Neural Networks and Learning Systems, 2022
A survey of community detection approaches: From statistical modeling to deep learning
D Jin, Z Yu, P Jiao, S Pan, D He, J Wu, SY Philip, W Zhang
IEEE Transactions on Knowledge and Data Engineering 35 (2), 1149-1170, 2021
What disease does this patient have? a large-scale open domain question answering dataset from medical exams
D Jin, E Pan, N Oufattole, WH Weng, H Fang, P Szolovits
Applied Sciences 11 (14), 6421, 2021
杨博 [1, 刘大有 [1, 金弟 [1, 马海宾 [1
软件学报 20 (1), 54-66, 2009
Semantic community identification in large attribute networks
X Wang, D Jin, X Cao, L Yang, W Zhang
Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016
A unified semi-supervised community detection framework using latent space graph regularization
L Yang, X Cao, D Jin, X Wang, D Meng
IEEE transactions on cybernetics 45 (11), 2585-2598, 2014
Graph neural networks for graphs with heterophily: A survey
X Zheng, Y Wang, Y Liu, M Li, M Zhang, D Jin, PS Yu, S Pan
arXiv preprint arXiv:2202.07082, 2022
Heterogeneous graph neural network via attribute completion
D Jin, C Huo, C Liang, L Yang
Proceedings of the web conference 2021, 391-400, 2021
Graph convolutional networks meet markov random fields: Semi-supervised community detection in attribute networks
D Jin, Z Liu, W Li, D He, W Zhang
Proceedings of the AAAI conference on artificial intelligence 33 (01), 152-159, 2019
Joint identification of network communities and semantics via integrative modeling of network topologies and node contents
D He, Z Feng, D Jin, X Wang, W Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
Adaptive community detection incorporating topology and content in social networks
M Qin, D Jin, D He, B Gabrys, K Musial
Proceedings of the 2017 IEEE/ACM International Conference on Advances in …, 2017
A Markov random walk under constraint for discovering overlapping communities in complex networks
D Jin, B Yang, C Baquero, D Liu, D He, J Liu
Journal of Statistical Mechanics: Theory and Experiment 2011 (05), P05031, 2011
Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization
X Cao, X Wang, D Jin, Y Cao, D He
Scientific reports 3 (1), 2993, 2013
Topology Optimization based Graph Convolutional Network.
L Yang, Z Kang, X Cao, Di Jin 0001, B Yang, Y Guo
IJCAI, 4054-4061, 2019
Community-centric graph convolutional network for unsupervised community detection
D He, Y Song, D Jin, Z Feng, B Zhang, Z Yu, W Zhang
Proceedings of the twenty-ninth international conference on international …, 2021
Universal graph convolutional networks
D Jin, Z Yu, C Huo, R Wang, X Wang, D He, J Han
Advances in Neural Information Processing Systems 34, 10654-10664, 2021
Semi-supervised community detection based on non-negative matrix factorization with node popularity
X Liu, W Wang, D He, P Jiao, D Jin, CV Cannistraci
Information Sciences 381, 304-321, 2017
Genetic algorithm with local search for community mining in complex networks
D Jin, D He, D Liu, C Baquero
2010 22nd IEEE international conference on tools with artificial …, 2010
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Artiklar 1–20