עקוב אחר
Shuiwang Ji, Professor and Truchard Family Chair
Shuiwang Ji, Professor and Truchard Family Chair
Department of Computer Science & Engineering, Texas A&M University
כתובת אימייל מאומתת בדומיין tamu.edu - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
3D convolutional neural networks for human action recognition‏
S Ji, W Xu, M Yang, K Yu‏
IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (1), 221-231, 2013‏
76772013
Graph U-Nets‏
H Gao, S Ji‏
The 36th International Conference on Machine Learning, 2083-2092, 2019‏
15052019
Deep convolutional neural networks for multi-modality isointense infant brain image segmentation‏
W Zhang, R Li, H Deng, L Wang, W Lin, S Ji, D Shen‏
NeuroImage 108, 214-224, 2015‏
9782015
SLEP: Sparse learning with efficient projections‏
J Liu, S Ji, J Ye‏
Arizona State University 6 (491), 7, 2009‏
831*2009
Multi-task feature learning via efficient l2, 1-norm minimization‏
J Liu, S Ji, J Ye‏
arXiv preprint arXiv:1205.2631, 2012‏
8152012
Explainability in graph neural networks: A taxonomic survey‏
H Yuan, H Yu, S Gui, S Ji‏
IEEE transactions on pattern analysis and machine intelligence 45 (5), 5782-5799, 2022‏
8132022
Large-scale learnable graph convolutional networks‏
H Gao, Z Wang, S Ji‏
Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018‏
7272018
Towards deeper graph neural networks‏
M Liu, H Gao, S Ji‏
Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020‏
6842020
Deep learning based imaging data completion for improved brain disease diagnosis‏
R Li, W Zhang, HI Suk, L Wang, J Li, D Shen, S Ji‏
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014‏
6102014
An accelerated gradient method for trace norm minimization‏
S Ji, J Ye‏
Proceedings of the 26th annual international conference on machine learning …, 2009‏
5512009
On explainability of graph neural networks via subgraph explorations‏
H Yuan, H Yu, J Wang, K Li, S Ji‏
International conference on machine learning, 12241-12252, 2021‏
4652021
Self-supervised learning of graph neural networks: A unified review‏
Y Xie, Z Xu, J Zhang, Z Wang, S Ji‏
IEEE transactions on pattern analysis and machine intelligence 45 (2), 2412-2429, 2022‏
4452022
Xgnn: Towards model-level explanations of graph neural networks‏
H Yuan, J Tang, X Hu, S Ji‏
Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020‏
4402020
A robust deep model for improved classification of AD/MCI patients‏
F Li, L Tran, KH Thung, S Ji, D Shen, J Li‏
IEEE journal of biomedical and health informatics 19 (5), 1610-1616, 2015‏
3512015
Feature selection based on structured sparsity: A comprehensive study‏
J Gui, Z Sun, S Ji, D Tao, T Tan‏
IEEE transactions on neural networks and learning systems 28 (7), 1490-1507, 2016‏
3402016
Canonical correlation analysis for multilabel classification: A least-squares formulation, extensions, and analysis‏
L Sun, S Ji, J Ye‏
IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (1), 194-200, 2010‏
3382010
Spherical message passing for 3d molecular graphs‏
Y Liu, L Wang, M Liu, Y Lin, X Zhang, B Oztekin, S Ji‏
International Conference on Learning Representations (ICLR), 2022‏
333*2022
Position: TrustLLM: Trustworthiness in large language models‏
Y Huang, L Sun, H Wang, S Wu, Q Zhang, Y Li, C Gao, Y Huang, W Lyu, ...‏
International Conference on Machine Learning, 20166-20270, 2024‏
319*2024
Discriminant sparse neighborhood preserving embedding for face recognition‏
J Gui, Z Sun, W Jia, R Hu, Y Lei, S Ji‏
Pattern Recognition 45 (8), 2884-2893, 2012‏
3002012
Hypergraph spectral learning for multi-label classification‏
L Sun, S Ji, J Ye‏
Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008‏
3002008
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מאמרים 1–20