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Jiong Zhu
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2020 – today
- 2024
- [j6]Jueqi Guan, Xiao-Feng Wang, Wen-Zhuo Wang, Jiong Zhu, Gwo-Jen Hwang:
Creating in the metaverse: An SSRL-based collaborative painting approach to promote students' creativity, socially shared regulation and positive painting behaviours. J. Comput. Assist. Learn. 40(4): 1373-1388 (2024) - [c10]Charles Dickens, Edward W. Huang, Aishwarya Reganti, Jiong Zhu, Karthik Subbian, Danai Koutra:
Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training. WWW (Companion Volume) 2024: 1502-1510 - 2023
- [j5]Jiong Zhu, Yujun Yan, Mark Heimann, Lingxiao Zhao, Leman Akoglu, Danai Koutra:
Heterophily and Graph Neural Networks: Past, Present and Future. IEEE Data Eng. Bull. 46(2): 12-34 (2023) - [j4]Ying Huang, Gang Dong, Zhangyin Liu, Jiong Zhu, Weidong Peng:
Voice broadcast based on 5G sensor in urban fire emergency system application. J. Comput. Methods Sci. Eng. 23(3): 1363-1380 (2023) - [c9]Jiayin Huang, Wenjing Yue, Yiqiao Wang, Jiong Zhu, Liqiang Ni:
Syndrome-Aware Herb Recommendation with Heterogeneous Graph Neural Network. DASFAA (Workshops) 2023: 109-124 - [c8]Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik:
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). KDD 2023: 5870-5871 - [c7]Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra:
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks. LoG 2023: 6 - [i7]Jiong Zhu, Aishwarya Reganti, Edward W. Huang, Charles Dickens, Nikhil Rao, Karthik Subbian, Danai Koutra:
Simplifying Distributed Neural Network Training on Massive Graphs: Randomized Partitions Improve Model Aggregation. CoRR abs/2305.09887 (2023) - [i6]Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra:
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks. CoRR abs/2306.05557 (2023) - [i5]Charles Dickens, Eddie W. Huang, Aishwarya Reganti, Jiong Zhu, Karthik Subbian, Danai Koutra:
Graph Coarsening via Convolution Matching for Scalable Graph Neural Network Training. CoRR abs/2312.15520 (2023) - 2022
- [c6]Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra:
How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications. KDD 2022: 2637-2647 - [i4]Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra:
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods. CoRR abs/2207.04376 (2022) - 2021
- [j3]Yi Xuan, Weiguo Si, Jiong Zhu, Zhiqing Sun, Jian Zhao, Mingjie Xu, Shouliang Xu:
Multi-Model Fusion Short-Term Load Forecasting Based on Random Forest Feature Selection and Hybrid Neural Network. IEEE Access 9: 69002-69009 (2021) - [j2]Yuncong Zhao, Yuan Zhang, Hongyan Wang, Xin Du, Qiangzi Li, Jiong Zhu:
Intraday Variation Mapping of Population Age Structure via Urban-Functional-Region-Based Scaling. Remote. Sens. 13(4): 805 (2021) - [c5]Jiong Zhu, Ryan A. Rossi, Anup Rao, Tung Mai, Nedim Lipka, Nesreen K. Ahmed, Danai Koutra:
Graph Neural Networks with Heterophily. AAAI 2021: 11168-11176 - [i3]Jiong Zhu, Junchen Jin, Michael T. Schaub, Danai Koutra:
Improving Robustness of Graph Neural Networks with Heterophily-Inspired Designs. CoRR abs/2106.07767 (2021) - 2020
- [c4]Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra:
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs. NeurIPS 2020 - [i2]Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu, Danai Koutra:
Generalizing Graph Neural Networks Beyond Homophily. CoRR abs/2006.11468 (2020) - [i1]Jiong Zhu, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Nesreen K. Ahmed, Danai Koutra:
Graph Neural Networks with Heterophily. CoRR abs/2009.13566 (2020)
2010 – 2019
- 2019
- [j1]Xinzheng Xu, Tianming Liang, Jiong Zhu, Dong Zheng, Tongfeng Sun:
Review of classical dimensionality reduction and sample selection methods for large-scale data processing. Neurocomputing 328: 5-15 (2019) - [c3]Yujun Yan, Jiong Zhu, Marlena Duda, Eric Solarz, Chandra Sekhar Sripada, Danai Koutra:
GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data. KDD 2019: 772-782 - 2010
- [c2]Zhaoqiang Lai, Jiaxi Hu, Chang Liu, Vahid Taimouri, Darshan Pai, Jiong Zhu, Jianrong Xu, Jing Hua:
Intra-Patient Supine-Prone Colon Registration in CT Colonography Using Shape Spectrum. MICCAI (1) 2010: 332-339
2000 – 2009
- 2006
- [c1]Satoshi Tamura, Koji Hashimoto, Jiong Zhu, Satoru Hayamizu, Hirotsugu Asai, Hideki Tanahashi, Makoto Kanagawa:
Automatic metadata generation and video editing based on speech and image recognition for medical education contents. INTERSPEECH 2006
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