Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence
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Preprints

2025

  • N. Bar, M. Seleznova, Y. Alexander, G. Kutyniok, R. Giryes. Revisiting Glorot Initialization for Long-Range Linear Recurrences. (arXiv:2505.19827)
  • V. Fojtik, M. Matveev, H. Chou, G. Kutyniok, J. Maly. Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization. (arXiv:2505.21423)
  • M. Seleznova, H. Chou, M. Verdun, G. Kutyniok. GradPCA: Leveraging NTK Alignment for Reliable Out-of-Distribution Detection. (arXiv:2505.16017)
  • J. Lee and G. Kutyniok. Expressivity of Deep Neural Networks. (pdf)
  • Sustainable AI: Mathematical Foundations of Spiking Neural Networks. A. Fono, M. Singh, E. Araya, P. Petersen, H. Boche, G. Kutyniok. (arXiv:2503.02013v1)
  • C. Bülte, Y. Sale, T. Löhr, P. Hofman, G. Kutyniok, E. Hüllermeier. An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression. (arXiv:2504.18433)
  • P. Scholl, A. Dietrich, S. Wolf, J. Lee, A. Schäffer, G. Kutyniok, M. Iskandar. Interpretable Robotic Friction Learning via Symbolic Regression. (arXiv:2505.13186)

2024

P. Scholl, A. Bacho, H. Boche, G. Kutyniok. Symbolic Recovery of Differential Equations: The Identifiability Problem (arXiv:2210.08342)

2023

  • S. Kolek, A. Chattopadhyay, K. Chan, H. Andrade-Loarca, G. Kutyniok, R. Vidal. Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. (arXiv:2312.11548)
  • M. Singh, A. Fono, G. Kutyniok. Expressivity of Spiking Neural Networks (arXiv:2308.08218)
  • H. Andrade-Loarca, J. Hege, A. Bacho, G. Kutyniok. PoissonNet: Resolution-Agnostic 3D Shape Reconstruction using Fourier Neural Operators (arXiv:2308.01766)
  • A. Bacho, H. Boche, G. Kutyniok. Reliable AI: Does the Next Generation Require
    Quantum Computing? (arXiv:2307.01301v1)
  • Hung-Hsu Chou, Johannes Maly, Claudio Mayrink Verdun. Non-negative Least Squares via Overparametrization (arXiv:2207.08437)

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