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Department of Physics and Technology gitta.a.kutyniok@uit.no

Gitta Astrid Hildegard Kutyniok


Adjunct Professor / Machine Learning


  • Sohir Maskey, Ron Levie, Gitta Astrid Hildegard Kutyniok :
    Transferability of graph neural networks: An extended graphon approach
    Applied and Computational Harmonic Analysis 2023 ARKIV / DOI
  • Ron Levie, Haim Avron, Gitta Astrid Hildegard Kutyniok :
    Quasi Monte Carlo time-frequency analysis
    Journal of Mathematical Analysis and Applications 2023 ARKIV / DOI
  • Cagkan Yapar, Ron Levie, Gitta Astrid Hildegard Kutyniok, Giuseppe Caire :
    Real-Time Outdoor Localization Using Radio Maps: A Deep Learning Approach
    IEEE Transactions on Wireless Communications 2023 ARKIV / DOI
  • Héctor Andrade-Loarca, Gitta Astrid Hildegard Kutyniok, Ozan Öktem, Philipp Petersen :
    Deep microlocal reconstruction for limited-angle tomography
    Applied and Computational Harmonic Analysis 2022 ARKIV / DOI
  • Gitta Astrid Hildegard Kutyniok, Philipp Petersen, Mones Raslan, Reinhold Schneider :
    A Theoretical Analysis of Deep Neural Networks and Parametric PDEs
    Constructive approximation 2021 ARKIV / DOI
  • Stephan Wäldchen, Jan Macdonald, Sascha Hauch, Gitta Astrid Hildegard Kutyniok :
    The computational complexity of understanding binary classifier decisions
    The journal of artificial intelligence research 2021 ARKIV / DOI
  • Ali Hashemi, Chang Cai, Gitta Astrid Hildegard Kutyniok, Klaus R. Müller, Srikantan S. Nagarajan, Stefan Haufe :
    Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework
    NeuroImage 2021 ARKIV / FULLTEKST / DOI
  • Moritz Geist, Philipp Petersen, Mones Raslan, Reinhold Schneider, Gitta Astrid Hildegard Kutyniok :
    Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks
    Journal of Scientific Computing 2021 ARKIV / DOI
  • Van Tiep Do, Ron Levie, Gitta Astrid Hildegard Kutyniok :
    Analysis of simultaneous inpainting and geometric separation based on sparse decomposition
    Analysis and Applications 2021 DOI
  • Héctor Andrade-Loarca, Gitta Astrid Hildegard Kutyniok, Ozan Öktem :
    Shearlets as feature extractor for semantic edge detection: The model-based and data-driven realm: Shearlets for Semantic Edge Detection
    Proceedings of the Royal Society. Mathematical, Physical and Engineering Sciences 2020 ARKIV / DOI
  • Ingo Guhring, Gitta Astrid Hildegard Kutyniok, Philipp Petersen :
    Error bounds for approximations with deep ReLU neural networks in W s, p norms
    Analysis and Applications 2019 DOI

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