1. Sparse recovery of elliptic solvers from matrix-vector products
    Florian Schäfer, and Houman Owhadi
    SIAM Journal on Scientific Computing 2024
  2. Fast Macroscopic Forcing Method
    Spencer H Bryngelson, Florian Schäfer, Jessie Liu, and Ali Mani
    Journal of Computational Physics 2024
  3. Lightning-fast Method of Fundamental Solutions
    Jiong Chen, Florian Schäfer, and Mathieu Desbrun
    ACM Transactions on Graphics (TOG) 2024


  1. Information geometric regularization of the barotropic Euler equation
    Ruijia Cao, and Florian Schäfer
  2. Scalable Bayesian transport maps for high-dimensional non-Gaussian spatial fields
    Matthias Katzfuss, and Florian Schäfer
    Journal of the American Statistical Association 2023
  3. Variational sparse inverse Cholesky approximation for latent Gaussian processes via double Kullback-Leibler minimization
    Jian Cao, Myeongjong Kang, Felix Jimenez, Huiyan Sang, Florian Tobias Schaefer, and Matthias Katzfuss
    In International Conference on Machine Learning 2023
  4. Sparse Cholesky Factorization for Solving Nonlinear PDEs via Gaussian Processes
    Yifan Chen, Houman Owhadi, and Florian Schäfer
    Accepted at Mathematics of Computation 2023
  5. Sparse Cholesky factorization by greedy conditional selection
    Stephen Huan, Joseph Guinness, Matthias Katzfuss, Houman Owhadi, and Florian Schäfer
  6. Targeted computation of nonlocal closure operators via an adjoint-based macroscopic forcing method
    Jessie Liu, Florian Schäfer, Spencer H Bryngelson, Tamer A Zaki, and Ali Mani


  1. ZerO Initialization: Initializing Neural Networks with only Zeros and Ones
    Jiawei Zhao, Florian Schäfer, and Anima Anandkumar
    Transactions on Machine Learning Research 2022
  2. Competitive Physics Informed Networks
    Qi Zeng, Yash Kothari, Spencer H Bryngelson, and Florian Tobias Schaefer
    In The Eleventh International Conference on Learning Representations 2022


  1. Robust Reinforcement Learning: A Constrained Game-theoretic Approach
    Jing Yu, Clement Gehring, Florian Schäfer, and Animashree Anandkumar
    In Proceedings of the 3rd Conference on Learning for Dynamics and Control 2021
  2. Sparse Cholesky factorization by Kullback-Leibler minimization
    Florian Schäfer, Matthias Katzfuss, and Houman Owhadi
    SIAM Journal on Scientific Computing 2021
  3. Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity
    Florian Schäfer, T. J. Sullivan, and Houman Owhadi
    Multiscale Model. Simul. 2021
  4. Polymatrix Competitive Gradient Descent
    Jeffrey Ma, Alistair Letcher, Florian Schäfer, Yuanyuan Shi, and Anima Anandkumar
  5. Multiscale cholesky preconditioning for ill-conditioned problems
    Jiong Chen, Florian Schäfer, Jin Huang, and Mathieu Desbrun
    ACM Transactions on Graphics (TOG) 2021


  1. Competitive Mirror Descent
    Florian Schäfer, Anima Anandkumar, and Houman Owhadi
  2. Implicit competitive regularization in GANs
    Florian Schäfer, Hongkai Zheng, and Anima Anandkumar
    In the 37th International Conference on Machine Learning (ICML 2020) 2020


  1. Statistical numerical approximation
    Houman Owhadi, Clint Scovel, and Florian Schäfer
    Notices of the American Mathematical Society 2019
  2. Competitive gradient descent
    Florian Schäfer, and Anima Anandkumar
    Advances in Neural Information Processing Systems 2019


  1. Image extrapolation for the time discrete metamorphosis model – existence and applications
    Alexander Effland, Martin Rumpf, and Florian Schäfer
    SIAM Journal on Imaging Sciences 2018


  1. Time discrete extrapolation in a Riemannian space of images
    Alexander Effland, Martin Rumpf, and Florian Schäfer
    In International Conference on Scale Space and Variational Methods in Computer Vision 2017