Nick Heilenkötter

According to our database, Nick Heilenkötter authored at least 7 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Bayesian view on the training of invertible residual networks for solving linear inverse problems.

Clemens Arndt, Sören Dittmer, Nick Heilenkötter, Meira Iske, Tobias Kluth, Judith Nickel

CoRR, 2023

Equivariant Neural Networks for Indirect Measurements.

Matthias Beckmann, Nick Heilenkötter

CoRR, 2023

Invertible residual networks in the context of regularization theory for linear inverse problems.

Clemens Arndt, Alexander Denker, Sören Dittmer, Nick Heilenkötter, Meira Iske, Tobias Kluth, Peter Maass, Judith Nickel

CoRR, 2023

2022

Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems.

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

CoRR, 2022

2021

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

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

J. Imaging, 2021

Deeply supervised UNet for semantic segmentation to assist dermatopathological assessment of Basal Cell Carcinoma (BCC).

Jean Le'Clerc Arrastia, Nick Heilenkötter, Daniel Otero Baguer, Lena Hauberg-Lotte, Tobias Boskamp, Sonja Hetzer, Nicole Duschner, Jörg Schaller, Peter Maaß

CoRR, 2021

2019

Argument Search: Assessing Argument Relevance.

Martin Potthast, Lukas Gienapp, Florian Euchner, Nick Heilenkötter, Nico Weidmann, Henning Wachsmuth, Benno Stein, Matthias Hagen

Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019