Florian Schäfer

S1317 CODA

756 W Peachtree St

Atlanta, GA 30332

I’m Florian Schäfer, assistant professor in the School of Computational Science and Engineering at Georgia Tech.

Prior to joining Georgia Tech, I received my PhD in applied and computational mathematics at Caltech, working with Houman Owhadi. Before that, I received my Bachelor’s and Master’s degrees in Mathematics at the University of Bonn.

My research interests lie at the interface of numerical computation, statistical inference, and competitive games. To learn more, have a look at these high-level summaries or the defense of my thesis.

I am currently hiring PhD students. If you have a strong background in computational mathematics and the above seems interesting (or you have a project in mind that I might find interesting), feel free to reach out!

news

Sep 23, 2022 I will be at the Siam Conference on the Mathematics of Data Science in San Diego from Sep. 26-30. I’ll give a talk on locality-exploiting operator learning on Friday 11:00-12:25, as part of the minisymposium on “Fast and Scalable Bayesian Inference”. Stephen will also be there, and present his work on experimental design approaches to sparse linear algebra on Wednesday 3:15-3:40 in the minisymposium on “Kernel Methods for Computing and Learning”.
Sep 14, 2022 I gave a talk (virtually) at the seminar for mathematics in imaging, data, and optimization at RPI, thanks to Yangyang for inviting me! You can find the video of the talk here.
Jul 15, 2022 I will be at the CTR summer program from July 17th to August 12th, working with Spencer Bryngelson on using locality and causality for operator inference. Feel free to reach out if you are at Stanford during that time!
May 1, 2022 Competitive physics informed networks solve PDEs to accuracies previously out of reach for physics informed networks! Joint work with Qi Zeng and Spencer Bryngelson.
Apr 19, 2022 I’ll be giving a talk at the UPenn applied mathematics and computational science colloquium on Friday April 22nd.

selected publications

  1. Sparse Cholesky factorization by Kullback-Leibler minimization
    Schäfer, Florian, Katzfuss, Matthias, and Owhadi, Houman
    SIAM Journal on Scientific Computing 2021
    arXiv
  2. Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity
    Schäfer, Florian, Sullivan, T. J., and Owhadi, Houman
    Multiscale Model. Simul. 2021
    arXiv Blog
  3. Implicit competitive regularization in GANs
    Schäfer, Florian, Zheng, Hongkai, and Anandkumar, Anima
    In the 37th International Conference on Machine Learning (ICML 2020)
    arXiv Blog Slides
  4. Competitive Gradient Descent
    Schäfer, Florian, and Anandkumar, Anima
    In Advances in Neural Information Processing Systems 32
    arXiv HTML Blog