Yiping Lu

Ph.D. student

Institute for Computational and Mathematical Engineering
School Of Engineering
Stanford University

Bachelor of Science(Honor Track)

Department of Scientific & Engineering Computing
School of mathematical sciences
Peking University

Email: yplu [at] stanford [dot] edu
Contact: Moving now... contact me by email!

Talk Slides

Bolded ones are about my own research.

Lecture Notes

Lecture Notes

-Fourier Analysis: pdf -Wavelet-like Structure On Manifold And Graph: pdf
-Multigrid Methods: pdf -Convex Analysis And Variational Problems: pdf
-Deep Learning For Image Registration pdf -Coming soon...


A slide reviews my research on "ODE" and Deep Learning: [slide]

-Express Power Of Neural Networks: pdf -Deep Residual Learning: pdf
-Stochastic Learning Methods In Deep Learning: pdf -Asynchronous Parallel Iteration: pdf
-Differential Equation Modeling For Optimization: pdf -A Review On Deep Learning Theory: pdf
- Geometry Of Optimal Transport And WGAN: pdf -Rethinking kernel learning: pdf
-Neural ODE: pdf -Deep learning theory: pdf


  • Paper Reading Project: github

© Yiping Lu | Last updated: 04/01/2019

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Theory without practice is empty, but equally, practice without theory is blind. ---- I. Kant

People who wish to analyze nature without using mathematics must settle for a reduced understanding. ---- Richard Feynman