1. Zhixu Gao, Yanhong Chen, Xianzhi Ao, Fulu Yue, Hong Chen, et.al., ISNet:DecomposedDynamic Spatio‐TemporalNeural Network for Ionospheric Scintillation Forecasts, Space Weather 2025, DOI: 10.1029/2024SW004239.

2. Junpei Li, Hong Chen, Jingjing Wang, Yanhong Chen, Bingxian Luo, Hao Deng, A Novel Convolutional Neural Network–Long Short-term Memory Model for Interplanetary Coronal Mass Ejection Detection, The Astrophysical Journal Supplement Series (ApJS), 2025, 279:24, DOI: 10.3847/1538-4365/adde54.

3. Yutao Hu, Yulong Wang, Libing Wang, Han Li, Hong Chen, Yuan-Yan Tang, Tensor Nuclear Norm based Multi-channel Atomic Representation for Robust Face Recognition，IEEEE Transactions on Image Processing, 2025.

4. Yuxin Dong, Tieliang Gong, Hong Chen, Shuangyong Song, Weizhan Zhang, Chen Li. How Does Distribution Matching Help Domain Generalization: An Information-theoretic Analysis, IEEE Transactions on Information Theory , 2025, DOI: 10.1109/TIT.2025.3531136

5. Liyuan Liu, Yaohui Chen, Weifu Li, Yingjie Wang, Bin Gu, Feng Zheng, Hong Chen. Generalization Bounds of Deep Neural Networks With τ-Mixing Samples, IEEE Transactions on Neural Networks and Learning Systems, 2025, DOI: 10.1109/TNNLS.2025.3526235

6. ··Wen Wen, Han Li, Rui Wu, Lingjuan Wu, Hong Chen. Generalization analysis of adversarial pairwise learning. Neural Networks, 2024.

7. ··Hong Chen*, Xuelin Zhang, Tieliang Gong, Bin Gu, Feng Zheng. Error Density-dependent Empirical Risk Minimization. Expert Systems With Applications, 2024.

8. Yutao Hu, Yulong Wang, Han Li, Hong Chen. Robust multi-view learning via M-estimator joint sparse representation. Pattern Recognition, Volume 151, July 2024, 110355.

9. Liangxi Liu, Feng Zheng, Hong Chen, Guo-Jun Qi, Heng Huang, Ling Shao. A Bayesian Federated Learning Framework with Online Laplace Approximation. IEEE TPAMI, vol. 46, no. 1, pp. 1-16, Jan 2024.

10. Hao Deng, Yuting Zhong, Hong Chen, Jun Chen, Jingjing Wang, Yanhong Chen, Bingxian Luo. Two-stage Hierarchical Framework for Solar Flare Prediction. The Astrophysical Journal Supplement Series, 268:43 (12pp), 2023.

11. Yuxin Dong, Tieliang Gong, Hong Chen, Chen Li. Efficient Approximations for Matrix-based Rényi's Entropy on Sequential Data. IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2023.3314089.

12. Peipei Yuan, Xinge You, Hong Chen, Yingjie Wang, Qinmu Peng, Bin Zou. Sparse Additive Machine With the Correntropy-Induced Loss. IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2023.3280349.

13. Yulong Wang, Kit Ian Kou, Hong Chen, Yuan Yan Tang, Luoqing Li. Double Auto-weighted Tensor Robust Principal Component Analysis. IEEE Transactions on Image Processing, doi: 10.1109/TIP.2023.3310331.

14. Libin Wang, Yulong Wang, Hao Deng, Hong Chen. Attention reweighted sparse subspace clustering. Pattern Recognition, Volume 139, 109438, 2023.

15. Hong Chen, Youcheng Fu, Xue Jiang, Yanhong Chen, Weifu Li, Yicong Zhou, Feng Zheng. Gradient Learning with the Mode-induced Loss: Consistency Analysis and Applications. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.

16. Yuxiang Han, Hong Chen, Tieliang Gong, Jia Cai. Robust Partially Linear Models for Automatic Structure Discovery, Expert Systems with Applications, Volume 217, 1 May 2023, 119528

17. Linqian Han, Wanshun Zhong, Jia Qian, Minliang Jin, Peng Tian, Wanchao Zhu, Hongwei Zhang, Yonghao Sun, Jia-Wu Feng, Xiangguo Liu, Guo Chen, Babar Farid, Ruonan Li, Zimo Xiong, Zhihui Tian, Juan Li, Zi Luo, Dengxiang Du, Sijia Chen, Qixiao Jin, Jiaxin Li, Zhao Li, Yan Liang, Xiaomeng Jin, Yong Peng, Chang Zheng, Xinnan Ye, Yuejia Yin, Hong Chen, Weifu Li, Ling-Ling Chen, Qing Li, Jianbing Yan, Fang Yang & Lin Li. A multi-omics integrative network map of maize, Nature Genetics, 2023.

18. Yulong Wang, Kit Ian Kou, Hong Chen, Yuan Yan Tang, Luoqing Li. Simultaneous Robust Matching Pursuit for Multi-view Learning, Pattern Recognition,Volume 134:109100, 2023.

19. Yulong Wang, Yap-Peng Tan, Yuan Yan Tang, Hong Chen, Cuiming Zou, Luoqing Li. Generalized and Discriminative Collaborative Representation for Multiclass Classification, IEEE Transactions on Cybernetics,52(5):2675–2686, 2022.

20. Tieliang Gong, Yuxin Dong, Hong Chen, Bo Dong, Chen Li. Markov Subsampling Based on Huber Criterion. IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2022.3189069, 2022.

21. Jun Chen, Hao Deng, Shuxin Li, Weifu Li, Hong Chen, Yanhong Chen, Bingxian Luo. RU-net: A Residual U-net for Automatic Interplanetary Coronal Mass Ejection Detection. The Astrophysical Journal Supplement Series, 259(1):8, 2022.

22. Hong Chen, Yingjie Wang, Feng Zheng, Cheng Deng, Heng Huang. Sparse modal additive model. IEEE Transactions on Neural Networks and Learning Systems, 32(6): 2373-2387, 2021.

23. Hong Chen, Changying Guo,Yingjie Wang, Huijuan Xiong. Sparse additive machine with ramp loss. Analysis and Applications, 19(3):509-528, 2021.

24. Yulong Wang, Yuan Yan Tang, Luoqing Li, Hong Chen. Modal regression based atomic representation for robust face recognition and reconstruction, IEEE Transactions on Cybernetics,50(10):4393–4405, 2020.

25. Yulong Wang,Yuan-Yan Tang, Luoqing Li, Hong Chen, Jianjia Pan. Atomic representation-based classification: theory, algorithm and applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(1): 6–19, 2019.

26. Xiaoqian Wang, Hong Chen, Jingwen Yan, Kwangsik Nho, Shannon L Risacher, Andrew J Saykin, Li Shen, Heng Huang. Quantitative trait loci identification for brain endophenotypes via new additive model with random networks, Bioinformatics, 34(17): i866–i874, 2018.

27. Hong Chen, Yulong Wang. Kernel-based sparse regression with the correntropy-induced loss, Applied and Computational Harmonic Analysis, 44(1): 144–164, 2018.

28. Tieliang Gong, Zongben Xu, Hong Chen. Generalization analysis of Fredholm kernel regularized classifiers, Neural Computation, 29(7): 1879–1901, 2017.

29. Yicong Zhou#, Hong Chen#, Rushi Lan, Zhibin Pan. Generalization performance of regularized ranking with multiscale kernels, IEEE Transactions on Neural Networks and Learning Systems, 27: 993-1002, 2016. (#contributed equally)

30. Hong Chen, Jiangtao Peng, Yicong Zhou, Luoqing Li, Zhibin Pan. Extreme learning machine for ranking: Generalization analysis and applications, Neural Networks, 53: 110-126, 2014.

31. Hong Chen, Yi Tang, Luoqing Li, Yuan Yuan, Xuelong Li,Yuan Yan Tang, Error analysis of stochastic gradient descent ranking, IEEE Transactions on Cybernetics, 43: 898–909, 2013.

32. Hong Chen, Zhibin Pan, Luoqing Li, Yuan Yan Tang. Error analysis of coefficient-based regularized algorithm for density-level detection, Neural Computation, 25(4): 1107–1121, 2013.

33. Hong Chen, Yicong Zhou, Yuan Yan Tang, Luoqing Li, Zhibin Pan, Convergence rate of semi-supervised greedy algorithm, Neural Networks, 44–50, 2013.

34. Hong Chen. The convergence rate of a regularized ranking algorithm, Journal of Approximation Theory, 164: 1513–1519, 2012.

35. Hong Chen, Luoqing Li, Jiangtao Peng. Semi-supervised learning based on high density regions estimation, Neural Networks, 23(7): 812–818, 2010.

36. Hong Chen, Luoqing Li. Semi-supervised multi-category classification with imperfect model, IEEE Transactions on Neural Networks, 20(10): 1594–1603, 2009.