Bio


I am a Ph.D. student of Stanford Institute for Computational and Mathematical Engineering working with Lexing Ying and Jose Blanchet. I also work closely with Jianfeng Lu and Tatsunori Hashimoto. My research is supported by Stanford Interdisciplinary Graduate Fellowship.

My research lies in the intersection between optimal/stochastic control, statistics machine learning, applied analysis and computational physics.

More Information: https://sites.google.com/view/yipinglu2prime/home

All Publications


  • PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep network JOURNAL OF COMPUTATIONAL PHYSICS Long, Z., Lu, Y., Dong, B. 2019; 399
  • CURE: Curvature Regularization for Missing Data Recovery SIAM JOURNAL ON IMAGING SCIENCES Dong, B., Ju, H., Lu, Y., Shi, Z. 2020; 13 (4): 2169–88

    View details for DOI 10.1137/19M1261845

    View details for Web of Science ID 000600792700013

  • Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View CLR 2020 Workshop on Integration of Deep Neural Models and Differential Equations. Lu, Y., et al 2020
  • Dynamically Unfolding Recurrent Restorer: A Moving Endpoint Control Method for Image Restoration Seventh International Conference on Learning Representations(ICLR) 2019 Zhang, X., Lu, Y., Liu, J., Dong, B. 2019