our library

here every speaker is welcome to contribute with a couple of interesting references

  1. A Geometric Understanding of Deep Learning
    Na Lei, Dongsheng An, Yang Guo, Kehua Su, Shixia Liu, Zhongxuan Luo, Shing-Tung Yau, and Xianfeng Gu
    Engineering, 2020
  2. The Modern Mathematics of Deep Learning
    Julius Berner, Philipp Grohs, Gitta Kutyniok, and Philipp Petersen
    Dec 2022
  3. Topos and Stacks of Deep Neural Networks
    Jean-Claude Belfiore, and Daniel Bennequin
    Dec 2022
  4. Geometry of Data
    Parvaneh Joharinad, and Jürgen Jost
    Dec 2022
  5. The shape of things to come: Topological data analysis and biology, from molecules to organisms
    Erik J. Amézquita, Michelle Y. Quigley, Tim Ophelders, Elizabeth Munch, and Daniel H. Chitwood
    Developmental Dynamics, Dec 2020
  6. A User’s Guide to Topological Data Analysis
    Elizabeth Munch
    Journal of Learning Analytics, Jul 2017
  7. Advancing mathematics by guiding human intuition with AI
    Alex Davies, Petar Veličković, Lars Buesing, Sam Blackwell, Daniel Zheng, Nenad Tomašev, Richard Tanburn, Peter Battaglia, and 6 more authors
    Nature, Jul 2021