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2020 – today
- 2024
[c9]Daniel Coquelin
, Katharina Flügel, Marie Weiel, Nicholas Kiefer, Charlotte Debus, Achim Streit, Markus Götz:
Harnessing Orthogonality to Train Low-Rank Neural Networks. ECAI 2024: 2106-2113- [c8]Pavel Zwerschke, Arvid Weyrauch, Markus Götz, Charlotte Debus:
Taylor Expansion in Neural Networks: How Higher Orders Yield Better Predictions. ECAI 2024: 2983-2989 - [c7]Jan Debus, Charlotte Debus, Günther Dissertori, Markus Götz:
PETNet-Coincident Particle Event Detection using Spiking Neural Networks. NICE 2024: 1-9 - [c6]Muhammed Öz, Nicholas Kiefer, Charlotte Debus, Jasmin Hörter, Achim Streit, Markus Götz:
Model Fusion via Neuron Transplantation. ECML/PKDD (4) 2024: 3-19 - [i8]Daniel Coquelin, Katharina Flügel, Marie Weiel, Nicholas Kiefer, Charlotte Debus, Achim Streit, Markus Götz:
Harnessing Orthogonality to Train Low-Rank Neural Networks. CoRR abs/2401.08505 (2024) - [i7]Daniel Coquelin, Katherina Flügel, Marie Weiel, Nicholas Kiefer, Muhammed Öz, Charlotte Debus, Achim Streit, Markus Götz:
AB-Training: A Communication-Efficient Approach for Distributed Low-Rank Learning. CoRR abs/2405.01067 (2024) - [i6]Arvid Weyrauch, Thomas Steens, Oskar Taubert, Benedikt Hanke, Aslan Eqbal, Ewa Götz, Achim Streit, Markus Götz, Charlotte Debus:
ReCycle: Fast and Efficient Long Time Series Forecasting with Residual Cyclic Transformers. CoRR abs/2405.03429 (2024) - 2023
- [j4]Charlotte Debus, Marie Piraud, Achim Streit, Fabian J. Theis, Markus Götz:
Reporting electricity consumption is essential for sustainable AI. Nat. Mac. Intell. 5(11): 1176-1178 (2023) - [j3]Anis Farshian, Markus Götz, Gabriele Cavallaro, Charlotte Debus, Matthias Nießner, Jón Atli Benediktsson, Achim Streit:
Deep-Learning-Based 3-D Surface Reconstruction - A Survey. Proc. IEEE 111(11): 1464-1501 (2023) - [c5]Juan Pedro Gutiérrez H. Muriedas, Katharina Flügel, Charlotte Debus, Holger Obermaier, Achim Streit, Markus Götz:
perun: Benchmarking Energy Consumption of High-Performance Computing Applications. Euro-Par 2023: 17-31 - [c4]Oskar Taubert, Marie Weiel, Daniel Coquelin, Anis Farshian, Charlotte Debus, Alexander Schug, Achim Streit, Markus Götz:
Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations. ISC 2023: 106-124 - [i5]Oskar Taubert, Marie Weiel, Daniel Coquelin, Anis Farshian, Charlotte Debus, Alexander Schug, Achim Streit, Markus Götz:
Massively Parallel Genetic Optimization through Asynchronous Propagation of Populations. CoRR abs/2301.08713 (2023) - [i4]Katharina Flügel, Daniel Coquelin, Marie Weiel, Charlotte Debus, Achim Streit, Markus Götz:
Feed-Forward Optimization With Delayed Feedback for Neural Networks. CoRR abs/2304.13372 (2023) - 2022
- [j2]Daniel Coquelin, Charlotte Debus, Markus Götz, Fabrice von der Lehr, James Kahn, Martin Siggel, Achim Streit:
Accelerating neural network training with distributed asynchronous and selective optimization (DASO). J. Big Data 9(1): 14 (2022) - [c3]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:
Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads. ISC Workshops 2022: 108-121 - [i3]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:
Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads. CoRR abs/2212.01698 (2022) - 2021
- [i2]Daniel Coquelin, Charlotte Debus, Markus Götz, Fabrice von der Lehr, James Kahn, Martin Siggel, Achim Streit:
Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO). CoRR abs/2104.05588 (2021) - 2020
- [c2]Markus Götz, Charlotte Debus, Daniel Coquelin, Kai Krajsek, Claudia Comito, Philipp Knechtges, Björn Hagemeier, Michael Tarnawa, Simon Hanselmann, Martin Siggel, Achim Basermann, Achim Streit:
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics. IEEE BigData 2020: 276-287 - [c1]Ina Kompan, Charlotte Debus, Michael Ingrisch, Klaus H. Maier-Hein, Amir Abdollahi, Marco Nolden, Ralf Floca:
Abstract: MITK-ModelFit. Bildverarbeitung für die Medizin 2020: 81 - [i1]Markus Götz, Daniel Coquelin, Charlotte Debus, Kai Krajsek, Claudia Comito, Philipp Knechtges, Björn Hagemeier, Michael Tarnawa, Simon Hanselmann, Martin Siggel, Achim Basermann, Achim Streit:
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics. CoRR abs/2007.13552 (2020)
2010 – 2019
- 2019
- [j1]Charlotte Debus, Ralf Floca, Michael Ingrisch, Ina Kompan, Klaus H. Maier-Hein, Amir Abdollahi, Marco Nolden:
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. BMC Bioinform. 20(1): 31:1-31:18 (2019) - 2016
- [b1]Charlotte Debus:
Integrative multimodal image analysis using physical models for characterization of brain tumors in radiotherapy. Heidelberg University, Germany, 2016
Coauthor Index
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