Wissenschaftsschwerpunkt der

Peter-Maass
Prof. Peter Maaß

Weitere Informationen:

AG Technomathematik; ZeTeM

Publikationen
May 2024 // journal-article

Unsupervised Deep Feature Learning for Icequake Discrimination at Neumayer Station, Antarctica

Seismological Research Letters

Louisa Kinzel; Tanja Fromm; Vera Schlindwein; Peter Maass

Jan 2024 // journal-article

Score-Based Generative Models for PET Image Reconstruction

Machine Learning for Biomedical Imaging

Imraj RD Singh; Alexander Denker; Riccardo Barbano; Željko Kereta; Bangti Jin; Kris Thielemans; Peter Maass; Simon Arridge

Dec 2023 // journal-article

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; Tobias Kluth; Peter Maass; Judith Nickel

Oct 2023 // journal-article

Deep learning methods for partial differential equations and related parameter identification problems

Inverse Problems

Derick Nganyu Tanyu; Jianfeng Ning; Tom Freudenberg; Nick Heilenkötter; Andreas Rademacher; Uwe Iben; Peter Maass

Jun 2023 // journal-article

PatchNR: learning from very few images by patch normalizing flow regularization

Inverse Problems

Fabian Altekrüger; Alexander Denker; Paul Hagemann; Johannes Hertrich; Peter Maass; Gabriele Steidl

Dec 2022 // journal-article

Multimodal Lung Cancer Subtyping Using Deep Learning Neural Networks on Whole Slide Tissue Images and MALDI MSI

Cancers

Charlotte Janßen; Tobias Boskamp; Jean Le'Clerc Arrastia; Daniel Otero Baguer; Lena Hauberg-Lotte; Mark Kriegsmann; Katharina Kriegsmann; Georg Steinbuß; Rita Casadonte; Jörg Kriegsmann; Peter Maass

Jul 2022 // journal-article

StainCUT: Stain Normalization with Contrastive Learning

Journal of Imaging

José Carlos Gutiérrez Pérez; Daniel Otero Baguer; Peter Maass

Nov 2021 // journal-article

Conditional Invertible Neural Networks for Medical Imaging

Journal of Imaging

Alexander Denker; Maximilian Schmidt; Johannes Leuschner; Peter Maass

Apr 2021 // journal-article

Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma

Journal of Imaging

Jean Le’Clerc Arrastia; Nick Heilenkötter; Daniel Otero Baguer; Lena Hauberg-Lotte; Tobias Boskamp; Sonja Hetzer; Nicole Duschner; Jörg Schaller; Peter Maass

Mar 2021 // journal-article

Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications

Journal of Imaging

Johannes Leuschner; Maximilian Schmidt; Poulami Somanya Ganguly; Vladyslav Andriiashen; Sophia Bethany Coban; Alexander Denker; Dominik Bauer; Amir Hadjifaradji; Kees Joost Batenburg; Peter Maass; Maureen van Eijnatten

Jan 2021 // journal-article

Error analysis for filtered back projection reconstructions in Besov spaces

Inverse Problems

M Beckmann; P Maass; J Nickel

Dec 2020 // journal-article

Joint super-resolution image reconstruction and parameter identification in imaging operator: analysis of bilinear operator equations, numerical solution, and application to magnetic particle imaging

Inverse Problems

Tobias Kluth; Christine Bathke; Ming Jiang; Peter Maass

Jul 2020 // conference-paper

Conditional Normalizing Flows for Low-Dose Computed Tomography Image Reconstruction

ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models

DOI:

2020 // journal-article

Mathematical aspects of catalyst positioning in lithium/air batteries

Inverse Problems


2020 // journal-article

Using the chemical noise background in MALDI mass spectrometry imaging for mass alignment and calibration

Analytical Chemistry


2020 // journal-article

Regularization by architecture: A deep prior approach for inverse problems

Journal of Mathematical Imaging and Vision


2019 // conference-paper

On the Connection Between Adversarial Robustness and Saliency Map Interpretability

36th International Conference on Machine Learning

DOI:

2019 // journal-article

Solving inverse problems using data-driven models

Acta Numerica


2019 // conference-paper

Connection Between Shock Wave Induced Indentations and Hardness By Means Of Neural Networks

22nd International Conference on Material Forming (ESAFORM 2019)

DOI:

2019 // journal-article

Singular values for ReLU layers

IEEE Transactions on Neural Networks and Learning Systems

DOI:

2019 // book-chapter

Deep learning for trivial inverse problems

Compressed Sensing and its Applications


2018 // journal-article

A Survey on Surrogate Approaches to Non-negative Matrix Factorization

Vietnam Journal of Mathematics


2018 // book-chapter

Predictive compensation measures for the prevention of shape deviations of mircomilled dental products

Cold Micro Metal Forming

DOI:

2018 // journal-article

Targeted Feature Extraction in MALDI Mass Spectrometry Imaging to Discriminate Proteomic Profiles of Breast and Ovarian Cancer

Proteomics - Clinical Applications


2018 // conference-paper

Improving Generalization Properties of Measured System Matrices by Using Regularized Total Least Squares Reconstruction in MPI

International Workshop on Magnetic Particle Imaging (IWMPI) - Book of Abstrcts

DOI: