1.Akif, A., Staib, L., Herman, P., Rothman, D. L., Yu, Y., & Hyder, F. [2024] In vivo neuropil density from anatomical MRI and machine learning.Cerebral Cortex, 34(5).

2.Zhou R, Yu Y, Li C. [2024] Revealing neural dynamical structure of C. elegans with deep learning.Iscience, 2024, 27(5).

3.Qi, X., Zhang, X., Shen, H., Su, J., Gao, X., Li, Y., ... & Yu, Y. [2024] Switching of brain networks across different cerebral perfusion states: insights from EEG dynamic microstate analyses.Cerebral Cortex, 34(2), bhae035.

4.Yukun Zou, Xiaoxiao Peng, Wei Yang*, Jingdong Zhang, and Wei Lin [2024] Dynamics of simplicial SEIRS epidemic model: Global asymptotic stability and neural Lyapunov functions, Journal of Mathematical Biology (accepted May 25; published June 16), vol. 89, Art. no. 12.

5.Yongzheng Sun, Guanghui Wen, Haifeng Dai, Yu Feng, Sandro Azaele, Wei Lin*, and Fubao Zhou* [2024] Quantifying the resilience of coal energy supply in China towards carbon neutrality, RESEARCH, accepted May 11.

6.Shijie Zhou*, Xiaoxiao Peng, Wei Lin, and Xuerong Mao [2024] Adaptive control and synchronization of complex dynamical systems with various types of delays and stochastic disturbances, SIAM Journal on Applied Mathematics, accepted May 9.

7.Hongtai Jing, Zhengtao Gao, Sheng Xu, Tao Shen, Zhangzhi Peng, Shwai He, Tao You, Shuang Ye*, Wei Lin*, and Siqi Sun* [2024] Accurate prediction of antibody function and structure using bio-inspired antibody language model, Briefings in Bioinformatics (accepted May 6; published May 26), vol. 25, no. 4, Art. no. bbae245.

8.Xiaoxiao Peng and Shijie Zhou*[2024] Finite-time stochastic control for complex dynamical systems: The estimate for control time and energy consumption, Systems & Control Letters, 2024,184(2):105711.

9.Xu Huang, Zhiqiang Wang*, and Shijie Zhou[2024] The dichotomy property in stabilizability of $2 \times 2 $ linear hyperbolic systems, ESAIM: Control, Optimisation and Calculus of Variations, 2024, 30:24.

10.Xiaoxiao Peng, Shijie Zhou, Wei Lin*, and Xuerong Mao[2024] Invariance principles for G-brownian-motion-driven stochastic differential equations and their applications to G-stochastic control, SIAM Journal on Control and Optimization, 2024, 62(3):1569-1589.

11.Jingdong Zhang, Luan Yang, Qunxi Zhu* and Wei Lin* [2024] FESSNC: Fast exponentially stable and safe neural controller, 41st International Conference on Machine Learning (ICML 2024), accepted May 2.

12.Xin Li, Jingdong Zhang, Qunxi Zhu*, Chengli Zhao*, Xue Zhang, Xiaojun Duan, and Wei Lin [2024] From Fourier to neural ODEs: Flow matching for modeling complex systems, 41st International Conference on Machine Learning (ICML 2024), accepted May 2.

13.Qunxi Zhu* and Wei Lin [2024] Switched flow matching: Eliminating singularities via switching ODEs, 41st International Conference on Machine Learning (ICML 2024), accepted May 2.

14.Sizhe Yang, Xiaoru Sun, Li Jin*, Menghan Zhang*[2024] Inferring language dispersal patterns with velocity  field estimation. Nature Communications,2024,15, Article number: 190 

15.Xinyu Cheng, Dong Li, and Wen Yang* [2024] Localization for general Helmholtz, Journal of Differential Equations, February 26,accepted.

16.Xinyu Cheng, and Jiao Xu* [2024]On the global well-posedness and scattering of the 3D Klein–Gordon–Zakharov system, Calculus of Variations and Partial Differential Equations,accepted.

17.Yunzhang Li*, Xiaolu Tan, Shanjian Tang[2024] Discrete-time Approximation of Stochastic Optimal Control with Partial Observation, SIAM Journal on Control and Optimization,2024, 62(1): 326-350. 

18.Xin Li, Qunxi Zhu*, Chengli Zhao*, Xiaojun Duan, Bolin Zhao, Xue Zhang, Huanfei Ma, Jie Sun, and Wei Lin* [2024] Higher-order Granger reservoir computing: Simultaneously achieving scalable complex structures inference and accurate dynamics prediction, Nature Communications (accepted Feb. 28; published March 20), vol. 15, Art. no. 2506. (Editorially selected as a Featured Article both in NC's focus contents: AI & machine learning & Applied physics and mathematics)

19.Jingdong Zhang, Qunxi Zhu*, and Wei Lin* [2024]  Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation laws, Physical Review Research, Letter, January 25, accepted.

20.Xiaoxiao Peng, Shijie Zhou, Wei Lin*, and Xuerong Mao [2024] Invariance Principles for G-Brownian-Motion-Driven Stochastic Differential Equations and Their Applications to G-Stochastic Control, SIAM Journal on Control and Optimization (accepted January 12; published May 29), vol. 62, no. 3, pp. 1569-1589.

21.Min Yan, Can Huang, Peter Bienstman, Peter Tino, Wei Lin, and Jie Sun* [2024] Emerging opportunities and challenges for the future of reservoir computing, Nature Communications (accepted December 5; published March 6), vol. 15, Art. no. 2056. (Editorially selected as a Featured Article both in NC's focus contents: AI & machine learning.& Applied physics and mathematics)

22.Shijie Zhou, Wei Lin*, Xuerong Mao, and Jianhong Wu [2024] Generalized invariance principles for stochastic dynamical systems and their applications, IEEE Transactions on Automatic Control, Regular Paper, published in Early Access-May, 2023, vol. 69, no. 1, pp. 85-99.