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Prof. Dr. Bangti Jin

Ehemaliger Mitarbeiter der WG Industrial Mathematics


Research Areas

Theses (Selection)complete list

  1. Electrical Impedance Tomography with the complete electrode model and sparsity constraints (Matthias Gehre)

Publications (Selection)complete list

  1. D. Nganyu Tanyu, J. Ning, A. Hauptmann, B. Jin, P. Maaß.
    Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches.
    Zur Veröffentlichung eingereicht.

    online at: https://arxiv.org/abs/2310.18636

  2. A. Denker, I. Singh, R. Barbano, Z. Kereta, B. Jin, K. Thielemans, P. Maaß, S. Arridge.
    Score-Based Generative Models for PET Image Reconstruction.
    Erscheint in Machine Learning for Biomedical Imaging

    online at: https://arxiv.org/abs/2308.14190

  3. J. Antorán, R. Barbano, J. Leuschner, J. M. Hernández-Lobato, B. Jin.
    Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior.
    Transactions on Machine Learning Research, 12, 2023.

    online at: https://openreview.net/forum?id=FWyabz82fH

  4. R. Barbano, J. Antorán, J. Leuschner, J. M. Hernández-Lobato, B. Jin, Z. Kereta.
    Image Reconstruction via Deep Image Prior Subspaces.
    Zur Veröffentlichung eingereicht.

    online at: https://arxiv.org/abs/2302.10279

  5. M. Nittscher, M. F. Lameter, R. Barbano, J. Leuschner, B. Jin, P. Maaß.
    SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction.
    Medical Imaging with Deep Learning (MIDL 2023), 10.07.-12.07.2023.

    online at: https://2023.midl.io/papers/p014