Machine Learning and Dynamical Systems 

[9] Z. Song^, J. Yuan^, H. Yang*. FMint: Bridging Human Designed and Data Pretrained Models for Differential Equation Foundation Model. [pdf]

[8] Z. Jiang, C. Wang, H. Yang*. Finite Expression Methods for Discovering Physical Laws from Data. Submitted. [pdf]

[7] Y. Ong^, Z. Shen^, H. Yang^*. IAE-Net: Integral Autoencoders for Discretization-Invariant Learning. Journal of Machine Learning Research, 2022.  [pdf]

[6] Z. Huang, S. Liang, H. Zhang, H. Yang, L. Lin*, On Fast Simulation of Dynamical System with Neural Vector Enhanced Numerical Solver. Scientific Report, 2023  [pdf]

[5] Q. Du^, Y. Gu^, H. Yang^*, C. Zhou^. The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation. SIAM Journal on Numerical Analysis, 2022. [pdf]  [doi]

[4] S. Liang^, L. Lyu^, C. Wang ^, H. Yang^*. Reproducing Activation Function for Deep Learning. Submitted. [pdf] 

[3] Y. Ong, C. K. Chui, H. Yang*, CASS: Cross Adversarial Source Separation via Autoencoder. Submitted. [pdf] 

[2] J. Harlim^*, S. W. Jiang^, S. Liang^, H. Yang^. Machine Learning for Prediction with Missing Dynamics. Journal of Computational Physics, 2021 [pdf] [doi]

[1] J. Harlim^* and H. Yang^, Diffusion Forecasting Model with Basis Functions from QR Decomposition. Journal of Nonlinear Science, 2017. [pdf] [doi]

^: Equal contribution; *: Corresponding author.