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Markus Götz
Person information
- affiliation: Karlsruhe Institute of Technology (KIT), Steinbuch Centre for Computing (SCC), Germany
- affiliation: Jülich Supercomputing Center, Germany
- affiliation: University of Iceland, School of Engineering and Natural Sciences, Reykjavik, Iceland
- affiliation: Hasso Plattner Institute, Potsdam, Germany
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2020 – today
- 2024
- [c21]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 - [c20]Pavel Zwerschke, Arvid Weyrauch
Taylor Expansion in Neural Networks: How Higher Orders Yield Better Predictions. ECAI 2024: 2983-2989 - [c19]Jan Debus, Charlotte Debus, Günther Dissertori, Markus Götz
PETNet-Coincident Particle Event Detection using Spiking Neural Networks. NICE 2024: 1-9 - [c18]Muhammed Öz
Model Fusion via Neuron Transplantation. ECML/PKDD (4) 2024: 3-19 - [i10]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) - [i9]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) - [i8]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
- [j8]Charlotte Debus
Reporting electricity consumption is essential for sustainable AI. Nat. Mac. Intell. 5(11): 1176-1178 (2023) - [j7]Marie Piraud, Andrés Camero, Markus Götz
Providing AI expertise as an infrastructure in academia. Patterns 4(8): 100819 (2023) - [j6]Anis Farshian
Deep-Learning-Based 3-D Surface Reconstruction - A Survey. Proc. IEEE 111(11): 1464-1501 (2023) - [c17]Juan Pedro Gutiérrez H. Muriedas
perun: Benchmarking Energy Consumption of High-Performance Computing Applications. Euro-Par 2023: 17-31 - [c16]Oskar Taubert
Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations. ISC 2023: 106-124 - [i7]Oskar Taubert, Marie Weiel
Massively Parallel Genetic Optimization through Asynchronous Propagation of Populations. CoRR abs/2301.08713 (2023) - [i6]Katharina Flügel, Daniel Coquelin, Marie Weiel
Feed-Forward Optimization With Delayed Feedback for Neural Networks. CoRR abs/2304.13372 (2023) - 2022
- [j5]Daniel Coquelin
Accelerating neural network training with distributed asynchronous and selective optimization (DASO). J. Big Data 9(1): 14 (2022) - [j4]James Kahn
Learning tree structures from leaves for particle decay reconstruction. Mach. Learn. Sci. Technol. 3(3): 35012 (2022) - [c15]Yannick Funk, Markus Götz
Prediction of Optimal Solvers for Sparse Linear Systems Using Deep Learning. PP 2022: 14-24 - [c14]René Caspart
Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads. ISC Workshops 2022: 108-121 - [c13]Daniel Coquelin
Hyde: The First Open-Source, Python-Based, Gpu-Accelerated Hyperspectral Denoising Package. WHISPERS 2022: 1-5 - [i5]Daniel Coquelin, Behnood Rasti, Markus Götz, Pedram Ghamisi, Richard Gloaguen, Achim Streit:
HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising Package. CoRR abs/2204.06979 (2022) - [i4]James Kahn, Ilias Tsaklidis, Oskar Taubert, Lea Reuter, Giulio Dujany, Tobias Boeckh, Arthur Thaller, Pablo Goldenzweig, Florian Bernlochner, Achim Streit, Markus Götz:
Learning Tree Structures from Leaves For Particle Decay Reconstruction. CoRR abs/2208.14924 (2022) - [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
- [j3]Marie Weiel
Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions. Nat. Mach. Intell. 3(8): 727-734 (2021) - [c12]Daniel Coquelin
Evolutionary Optimization of Neural Architectures in Remote Sensing Classification Problems. IGARSS 2021: 1587-1590 - [i2]Daniel Coquelin, Charlotte Debus
Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO). CoRR abs/2104.05588 (2021) - 2020
- [c11]Markus Götz
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics. IEEE BigData 2020: 276-287 - [c10]Oskar Taubert, Markus Götz
Loss Scheduling for Class-Imbalanced Image Segmentation Problems. ICMLA 2020: 426-431 - [i1]Markus Götz
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics. CoRR abs/2007.13552 (2020)
2010 – 2019
- 2019
- [j2]Markus Götz
Automatic water mixing event identification in the Koljö fjord observatory data. Int. J. Data Sci. Anal. 7(1): 67-79 (2019) - 2018
- [j1]Markus Götz
Parallel Computation of Component Trees on Distributed Memory Machines. IEEE Trans. Parallel Distributed Syst. 29(11): 2582-2598 (2018) - [c9]Julius Lange, Gabriele Cavallaro, Markus Götz, Ernir Erlingsson, Morris Riedel:
The Influence of Sampling Methods on Pixel-Wise Hyperspectral Image Classification with 3D Convolutional Neural Networks. IGARSS 2018: 2087-2090 - 2017
- [c8]Matthias Book, Morris Riedel, Helmut Neukirchen, Markus Götz:
Facilitating collaboration in high-performance computing projects with an interaction room. SEPS@SPLASH 2017: 46-47 - 2016
- [c7]Christian Bodenstein, Markus Götz, Annika Jansen, Henrike Scholz, Morris Riedel
Automatic Object Detection Using DBSCAN for Counting Intoxicated Flies in the FLORIDA Assay. ICMLA 2016: 746-751 - 2015
- [c6]Markus Götz, Matthias Richerzhagen, Christian Bodenstein, Gabriele Cavallaro
On Scalable Data Mining Techniques for Earth Science. ICCS 2015: 2188-2197 - [c5]Gabriele Cavallaro, Morris Riedel
Scalable developments for big data analytics in remote sensing. IGARSS 2015: 1366-1369 - [c4]Morris Riedel
Scalable and parallel machine learning algorithms for statistical data mining - Practice & experience. MIPRO 2015: 204-209 - [c3]Markus Götz, Christian Bodenstein, Morris Riedel
HPDBSCAN: highly parallel DBSCAN. MLHPC@SC 2015: 2:1-2:10 - 2014
- [c2]Gabriele Cavallaro
Smart data analytics methods for remote sensing applications. IGARSS 2014: 1405-1408 - 2010
- [c1]Michael Goderbauer, Markus Götz, Alexander Großkopf, Andreas Meyer, Mathias Weske:
Syncro - Concurrent Editing Library for Google Wave. ICWE 2010: 510-513
Coauthor Index
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last updated on 2024-11-07 21:29 CET by the dblp team
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