Content
Preprints
2022
- E. Kasneci, K. Sessler, S. Küchemann, M. Bannert, D. Dementieva, F. Fischer, U. Gasser, G. Groh, S. Günnemann, E. Hüllermeier, S. Krusche, G. Kutyniok, T. Michaeli, C. Nerdel, J. Pfeffer, O. Poquet, M. Sailer, A. Schmidt, T. Seidel, M. Stadler, J. Weller, J. Kuhn, G. Kasneci. ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education. Learning & Individual Differences, to appear (pdf).
- Y. Lee, H. Boche, G. Kutyniok. Computability of Optimizers (arXiv:2301.06148)
- A. Bacho, H. Boche, G. Kutyniok. Complexity Blowup for Solutions of the Laplace and the Diffusion Equation. (arXiv:2212.00693)
- H. Boche, A. Fono and G. Kutyniok. Limitations of Deep Learning for Inverse Problems on Digital Hardware (arXiv:2202.13490)
- 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)
- M. Ko, U. K. Panchal, H. Andrade-Loarca, A. Mendez-Vazquez. CoShNet: A Hybird Complex Valued Neural Network using Shearlets (arXiv:2208.06882)
- H. Boche, A. Fono and G. Kutyniok. Non-Computability of the Pseudoinverse on Digital Computers (arXiv:2212.02940)
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)
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