Peter Maass
Universität Bremen
H-index: 43
Europe-Germany
Top articles of Peter Maass
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Smooth Deep Saliency | arXiv preprint arXiv:2404.02282 | Rudolf Herdt Maximilian Schmidt Daniel Otero Baguer Peter Maaß | 2024/4/2 |
How GAN Generators can Invert Networks in Real-Time | Rudolf Herdt Maximilian Schmidt Daniel Otero Baguer Jean Le’Clerc Arrastia Peter Maaß | 2024/2/27 | |
Svd-dip: Overcoming the overfitting problem in dip-based ct reconstruction | Marco Nittscher Michael Falk Lameter Riccardo Barbano Johannes Leuschner Bangti Jin | 2024/1/23 | |
Deep learning based histological classification of adnex tumors | European Journal of Cancer | Philipp Jansen Jean Le’Clerc Arrastia Daniel Otero Baguer Maximilian Schmidt Jennifer Landsberg | 2024/1/1 |
Invertible residual networks in the context of regularization theory for linear inverse problems | Inverse Problems | Clemens Arndt Alexander Denker Sören Dittmer Nick Heilenkötter Meira Iske | 2023/11/13 |
Score-based generative models for PET image reconstruction | arXiv preprint arXiv:2308.14190 | Imraj RD Singh Alexander Denker Riccardo Barbano Željko Kereta Bangti Jin | 2023/8/27 |
PatchNR: learning from very few images by patch normalizing flow regularization | Inverse Problems | Fabian Altekrüger Alexander Denker Paul Hagemann Johannes Hertrich Peter Maass | 2023/5/16 |
Einsatz künstlicher Intelligenz mittels Deep Learning in der dermatopathologischen Routinediagnostik des Basalzellkarzinoms: Applying an artificial intelligence … | JDDG: Journal der Deutschen Dermatologischen Gesellschaft | Nicole Duschner Daniel Otero Baguer Maximilian Schmidt Klaus Georg Griewank Eva Hadaschik | 2023/11 |
Model Stitching and Visualization How GAN Generators can Invert Networks in Real-Time | arXiv preprint arXiv:2302.02181 | Rudolf Herdt Maximilian Schmidt Daniel Otero Baguer Jean Le'Clerc Arrastia Peter Maass | 2023/2/4 |
Deep learning methods for partial differential equations and related parameter identification problems | arXiv e-prints | Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter Andreas Rademacher | 2022/12 |
Applying an artificial intelligence deep learning approach to routine dermatopathological diagnosis of basal cell carcinoma | JDDG: Journal der Deutschen Dermatologischen Gesellschaft | Nicole Duschner Daniel Otero Baguer Maximilian Schmidt Klaus Georg Griewank Eva Hadaschik | 2023/11 |
Neural representation of the stratospheric ozone chemistry | Environmental Data Science | Helge Mohn Daniel Kreyling Ingo Wohltmann Ralph Lehmann Peter Maass | 2023/1 |
DL4TO : A Deep Learning Library for Sample-Efficient Topology Optimization | David Erzmann Sören Dittmer Henrik Harms Peter Maaß | 2023/8/1 | |
Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches | arXiv preprint arXiv:2310.18636 | Derick Nganyu Tanyu Jianfeng Ning Andreas Hauptmann Bangti Jin Peter Maass | 2023/10/28 |
Parameter identification by deep learning of a material model for granular media | arXiv preprint arXiv:2307.04166 | Derick Nganyu Tanyu Isabel Michel Andreas Rademacher Jörg Kuhnert Peter Maass | 2023/7/9 |
Steerable conditional diffusion for out-of-distribution adaptation in imaging inverse problems | arXiv preprint arXiv:2308.14409 | Riccardo Barbano Alexander Denker Hyungjin Chung Tae Hoon Roh Simon Arrdige | 2023/8/28 |
Deep learning detection of melanoma metastases in lymph nodes | European Journal of Cancer | Philipp Jansen Daniel Otero Baguer Nicole Duschner Jean Le’Clerc Arrastia Maximilian Schmidt | 2023/7/1 |
Patchnr: Learning from small data by patch normalizing flow regularization | arXiv e-prints | Fabian Altekrüger Alexander Denker Paul Hagemann Johannes Hertrich Peter Maass | 2022/5 |
Selto: Sample-efficient learned topology optimization | arXiv preprint arXiv:2209.05098 | Sören Dittmer David Erzmann Henrik Harms Peter Maass | 2022/9/12 |
MALDI Imaging: Exploring the molecular landscape | Peter Maass Lena Hauberg-Lotte Tobias Boskamp | 2022/3/13 |
