Distgnn: Scalable distributed training for large-scale graph neural networks V Md, S Misra, G Ma, R Mohanty, E Georganas, A Heinecke, D Kalamkar, ... Proceedings of the International Conference for High Performance Computing …, 2021 | 102 | 2021 |
Deep graph similarity learning: A survey G Ma, NK Ahmed, TL Willke, PS Yu Data Mining and Knowledge Discovery 35, 688-725, 2021 | 80 | 2021 |
Kernelized support tensor machines L He, CT Lu, G Ma, S Wang, L Shen, SY Philip, AB Ragin International Conference on Machine Learning, 1442-1451, 2017 | 60 | 2017 |
Robust Spammer Detection by Nash Reinforcement Learning Y Dou, G Ma, PS Yu, S Xie Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 56 | 2020 |
Deep graph similarity learning for brain data analysis G Ma, NK Ahmed, TL Willke, D Sengupta, MW Cole, NB Turk-Browne, ... Proceedings of the 28th ACM International Conference on Information and …, 2019 | 56 | 2019 |
Ddgcn: Dual dynamic graph convolutional networks for rumor detection on social media M Sun, X Zhang, J Zheng, G Ma Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4611-4619, 2022 | 52 | 2022 |
Multi-view graph embedding with hub detection for brain network analysis G Ma, CT Lu, L He, SY Philip, AB Ragin 2017 IEEE International Conference on Data Mining (ICDM), 967-972, 2017 | 49 | 2017 |
Multi-view clustering with graph embedding for connectome analysis G Ma, L He, CT Lu, W Shao, PS Yu, AD Leow, AB Ragin Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 49 | 2017 |
Adversarial Attack on Hierarchical Graph Pooling Neural Networks H Tang, G Ma, Y Chen, L Guo, W Wang, B Zeng, L Zhan arXiv preprint arXiv:2005.11560, 2020 | 35 | 2020 |
Spatio-temporal tensor analysis for whole-brain fmri classification G Ma, L He, CT Lu, PS Yu, L Shen, AB Ragin Proceedings of the 2016 SIAM International Conference on Data Mining, 819-827, 2016 | 34 | 2016 |
Community-preserving graph convolutions for structural and functional joint embedding of brain networks J Liu, G Ma, F Jiang, CT Lu, SY Philip, AB Ragin 2019 IEEE International Conference on Big Data (Big Data), 1163-1168, 2019 | 26 | 2019 |
CommPOOL: An interpretable graph pooling framework for hierarchical graph representation learning H Tang, G Ma, L He, H Huang, L Zhan Neural Networks 143, 669-677, 2021 | 25 | 2021 |
Multi-graph clustering based on interior-node topology with applications to brain networks G Ma, L He, B Cao, J Zhang, PS Yu, AB Ragin Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016 | 22 | 2016 |
A convolutional neural network with pixel-wise sparse graph reasoning for COVID-19 lesion segmentation in CT images H Jia, H Tang, G Ma, W Cai, H Huang, L Zhan, Y Xia Computers in Biology and Medicine 155, 106698, 2023 | 16 | 2023 |
Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model H Tang, G Ma, L Guo, X Fu, H Huang, L Zhan IEEE Transactions on Neural Networks and Learning Systems, 2022 | 16 | 2022 |
Explainable Survival Analysis with Convolution-Involved Vision Transformer Y Shen, L Liu, Z Tang, Z Chen, G Ma, J Dong, X Zhang, L Yang, Q Zheng Proceedings of the AAAI Conference on Artificial Intelligence 36 (2), 2207-2215, 2022 | 11 | 2022 |
Line graph contrastive learning for link prediction Z Zhang, S Sun, G Ma, C Zhong Pattern Recognition 140, 109537, 2023 | 10 | 2023 |
PSGR: Pixel-wise Sparse Graph Reasoning for COVID-19 Pneumonia Segmentation in CT Images H Jia, H Tang, G Ma, W Cai, H Huang, L Zhan, Y Xia arXiv preprint arXiv:2108.03809, 2021 | 10 | 2021 |
A Distributed Graph-Theoretic Framework for Automatic Parallelization in Multi-core Systems G Ma, Y Xiao, T Willke, N Ahmed, S Nazarian, P Bogdan Proceedings of Machine Learning and Systems 3, 550-568, 2021 | 10 | 2021 |
Securing behavior-based opinion spam detection S Ge, G Ma, S Xie, SY Philip 2018 IEEE International Conference on Big Data (Big Data), 112-117, 2018 | 10 | 2018 |