Charlotte Debus

According to our database, Charlotte Debus authored at least 12 papers between 2016 and 2024.

Collaborative distances:

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

2024

Harnessing Orthogonality to Train Low-Rank Neural Networks.

Daniel Coquelin, Katharina Flügel, Marie Weiel, Nicholas Kiefer, Charlotte Debus, Achim Streit, Markus Götz

CoRR, 2024

2023

Deep-Learning-Based 3-D Surface Reconstruction - A Survey.

Anis Farshian, Markus Götz, Gabriele Cavallaro, Charlotte Debus, Matthias Nießner, Jón Atli Benediktsson, Achim Streit

Proc. IEEE, November, 2023

Reporting electricity consumption is essential for sustainable AI.

Charlotte Debus, Marie Piraud, Achim Streit, Fabian J. Theis, Markus Götz

Nat. Mac. Intell., November, 2023

Feed-Forward Optimization With Delayed Feedback for Neural Networks.

Katharina Flügel, Daniel Coquelin, Marie Weiel, Charlotte Debus, Achim Streit, Markus Götz

CoRR, 2023

Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations.

Oskar Taubert, Marie Weiel, Daniel Coquelin, Anis Farshian, Charlotte Debus, Alexander Schug, Achim Streit, Markus Götz

Proceedings of the High Performance Computing - 38th International Conference, 2023

perun: Benchmarking Energy Consumption of High-Performance Computing Applications.

Juan Pedro Gutiérrez H. Muriedas, Katharina Flügel, Charlotte Debus, Holger Obermaier, Achim Streit, Markus Götz

Proceedings of the Euro-Par 2023: Parallel Processing - 29th International Conference on Parallel and Distributed Computing, Limassol, Cyprus, August 28, 2023

2022

Accelerating neural network training with distributed asynchronous and selective optimization (DASO).

Daniel Coquelin, Charlotte Debus, Markus Götz, Fabrice von der Lehr, James Kahn, Martin Siggel, Achim Streit

J. Big Data, 2022

Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads.

René Caspart, Sebastian Ziegler, Arvid Weyrauch, Holger Obermaier, Simon Raffeiner, Leon Pascal Schuhmacher, Jan Scholtyssek, Darya Trofimova, Marco Nolden, Ines Reinartz, Fabian Isensee, Markus Götz, Charlotte Debus

Proceedings of the High Performance Computing. ISC High Performance 2022 International Workshops - Hamburg, Germany, May 29, 2022

2020

Abstract: MITK-ModelFit.

Ina Kompan, Charlotte Debus, Michael Ingrisch, Klaus H. Maier-Hein, Amir Abdollahi, Marco Nolden, Ralf Floca

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics.

Markus Götz, Charlotte Debus, Daniel Coquelin, Kai Krajsek, Claudia Comito, Philipp Knechtges, Björn Hagemeier, Michael Tarnawa, Simon Hanselmann, Martin Siggel, Achim Basermann, Achim Streit

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging - design, implementation and application on the example of DCE-MRI.

Charlotte Debus, Ralf Floca, Michael Ingrisch, Ina Kompan, Klaus H. Maier-Hein, Amir Abdollahi, Marco Nolden

BMC Bioinform., 2019

2016

Integrative multimodal image analysis using physical models for characterization of brain tumors in radiotherapy

Charlotte Debus

PhD thesis, 2016