Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence
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Preprints

2022

  • Y. Zhou, G. Kutyniok, B. Ribeiro. OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs (arXiv:2205.15117)
  • S. Maskey, Y. Lee, R. Levie, and G. Kutyniok. Stability and Generalization Capabilities of Message Passing Graph Neural Networks (arXiv:2202.00645)
  • H. Boche, A. Fono and G. Kutyniok. Limitations of Deep Learning for Inverse Problems on Digital Hardware (arXiv:2202.13490)
  • G. Kutyniok, An Introduction to the Mathematics of Deep Learning (pdf)
  • G. Kutyniok, The Mathematics of Artificial Intelligence (pdf)
  • H. Boche, A. Fono and G. Kutyniok. Inverse Problems Are Solvable on Real Number Signal Processing Hardware (arxiv:2204.02066)

2021

  • R. Levie, H. Avron, and G. Kutyniok. Quasi Monte Carlo Time-Frequency Analysis (arXiv:2011.02025)
  • C. Yapar, R. Levie, G. Kutyniok, and G. Caire. Real-time Outdoor Localization Using Radio Maps: A Deep Learning Approach (arXiv:2106.12556)
  • S. Maskey, R. Levie, and G. Kutyniok. Transferability of Graph Neural Networks: an Extended Graphon Approach. (arXiv:2109.10096)
  • S. Kolek, D. Nguyen, R. Levie, J. Bruna, G. Kutyniok. Cartoon Explanations of Image Classifiers (arXiv:2110.03485)