For a full list, please refer to my google citation.

Working Papers:

Almost sure convergence rates analysis and saddle avoidance of stochastic gradient methods, an abridged version appeared in COLT, 2022.

Selected Journal Papers: (By topics)

System Identification and Optimization Theory

Y. Yuan, X. Tang, W. Zhou, W. Pan, X. Li, H. Zhang, H. Ding and J. Goncalves. Data driven discovery of cyber physical systems, Nature Communications, 2019. Code+data

Z. Zeng, Z. Yue, A. Mauroy, J. Goncalves, Y. Yuan*, A sampling theorem for exact identification of continuous-time nonlinear dynamical systems, to appear, IEEE Transactions on Automatic Control, 2024.

Y. Yuan, G. Stan, S. Warnick and J. Goncalves , Robust dynamical network structure reconstruction, Automatica, 2011.

Y. Yuan, G. Stan, L. Shi, M. Barahona and J. Goncalves, Decentralised minimum-time consensus, Automatica, 2013.

D. Hayden, Y. Yuan* and J. Goncalves, Network identifiability from intrinsic noise, IEEE Transactions on Automatic Control, 2016.

Y. Yuan, M. Li, J. Liu and C. Tomlin, On the Powerball method: variants of descent methods for accelerated optimization, IEEE Control Systems Letters, 2019.

W. Pan, Y. Yuan, J. Goncalves and G. Stan, Bayesian approaches to the identification of nonlinear state-space systems, IEEE Transactions on Automatic Control, 2016.

Y. Wang, H. Fang, J. Jin, G. Ma, X. He, X. Dai, Z. Yue, C. Cheng, H. Zhang, D. Pu, D. Wu, Y. Yuan*, J. Gonçalves, J. Kurths, H. Ding, Data-driven discovery of stochastic differential equations, Engineering, 2022.

Y. Yuan, X. Li, L. Li, F. Jiang, X. Tang, F. Zhang, J. Goncalves, H. U. Voss, H. Ding, and J. Kurths, Machine discovery of partial differential equations from spatiotemporal data, Chaos, 2023. Code+data

Applitions to Cyber-physical Systems:

= industrial systems

G. Ma, S. Xu, B. Jiang, C. Cheng, X. Yang, Y. Shen, T. Yang, Y. Huang, H. Ding, Y. Yuan*, Real-time personalized health status prediction of lithium-ion batteries using deep transfer learning, Energy & Environmental Science, 2022. (Cover)

Y. Yuan, G. Ma, C. Cheng, B. Zhou, H. Zhao, H. ZHang, H. Ding, A general end-to-end diagnosis framework for manufacturing systems, National Science Review, 2020. Code+data

C. Cheng, G. Ma, Y. Zhang, M. Sun, F. Teng, H. Ding and Y. Yuan*, A deep learning-based remaining useful life prediction approach for bearings, IEEE/ASME Transactions on Mechatronics, 2020.

Y. Yuan, H. Zhang, Y. Wu, T. Zhu and H. Ding, Bayesian learning-based model predictive vibration control for thin-walled workpiece machining processes, IEEE/ASME Transactions on Mechatronics, 2017.

Y. Yuan, S. Low, O. Ardakanian and C. Tomlin, Inverse power flow problem, IEEE Transactions on Control of Network Systems, 2022.

Y. Yuan, J. Liu, D. Jin, Z. Yue, T. Yang, R. Chen, M. Wang, C. Sun, L. Xu, F. Hua, Y. Guo, X. Tang, X. He, X. Yi, D. Li, G. Wen, W. Yu, H.-T. Zhang, T. Chai, S. Sui and H. Ding, DeceFL: A principled fully decentralized federated learning framework, National Science Open, 2022. (Cover)

= natural and healthcare systems

L. Yan, H. Zhang, J. Goncalves, …, S. Li, H. Xu, and Y. Yuan*, An interpretable mortality prediction model for COVID-19 patients, Nature Machine Intelligence, 2020. Code, Web-interface.

H. Zhu, C. Cheng, …, X. Yang, and Y. Yuan*, Automatic multi-label ECG diagnosis of impulse or conduction abnormalities with deep learning: a cohort study, Lancet Digital Health, 2020.

E. Herrero, E. Kolmos, N. Bujdoso, Y. Yuan, …, A. Webb, J. Gonçalves and S. Davis, Early Flowering4 recruitment of Early Flowering3 in the nucleus sustains the Arabidopsis circadian clock, the Plant Cell, 2012.

Selected Conference Papers:

J. Liu and Y. Yuan, On almost sure convergence rates of stochastic gradient methods, COLT, 2022.

Y. Shen, Y. Hong, W. Zhou, R. Tai, Y. Yuan* and H. Ding, “Manipulability and robustness optimization of the cable-driven redundant soft manipulator,” IEEE Robio, 2021. (Best Student Paper Award, Finalist)

Q. Tao, J. Wang, Z. Xu, T. Lin, Y. Yuan and F. Zhang, “Swing-reducing flight control system for an underactuated indoor miniature autonomous blimp,” IEEE/ASME AIM, 2021. (Best Student Paper Award)

B. Zhou, J. Liu, W. Sun, R. Chen, C. Tomlin and Y. Yuan*, “pbSGD: Powered stochastic gradient descent methods for accelerated nonconvex optimization,” IJCAI, 2020.

L. Yao, Y. Yuan*, S. Sundaram and T. Yang, “Distributed finite-time optiization,” IEEE ICCA, 2018. (Best Student Paper Award)

O. Ardakanian, Y. Yuan*, R. Dobbe, A. von Meier, S. Low and C. Tomlin, “Event detection and localization in distribution grids with phasor measurement units,” IEEE PES GM, 2017. (Best of the Best Conference Paper Award)

Y. Yuan, J. Liu, R. M. Murray and J. Goncalves, “Minimal-time dynamical consensus,” ACC, 2012.

Y. Yuan and L. Shi, “Minimum sensor duty cycle with guaranteed estimator performance,” IEEE ICIA, 2012. (Best Paper Award, Finalist)

^* Corresponding author.