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Guixiang Ma
Guixiang Ma
Research Scientist, Intel Labs
Verified email at intel.com
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Year
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
932021
Deep graph similarity learning: A survey
G Ma, NK Ahmed, TL Willke, PS Yu
Data Mining and Knowledge Discovery 35, 688-725, 2021
742021
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
582017
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
542020
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
542019
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
492017
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
492017
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
442022
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
332020
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
332016
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
252019
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
242021
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
222016
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
152023
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
152022
Line graph contrastive learning for link prediction
Z Zhang, S Sun, G Ma, C Zhong
Pattern Recognition 140, 109537, 2023
102023
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
102021
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
102021
Similarity Learning with Higher-Order Graph Convolutions for Brain Network Analysis
G Ma, NK Ahmed, T Willke, D Sengupta, MW Cole, NB Turk-Browne, ...
arXiv preprint arXiv:1811.02662, 2018
102018
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
92022
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