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Daniel Coquelin
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2020 – today
- 2024
- [c5]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 - [i7]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) - [i6]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) - 2023
- [c4]Oskar Taubert
Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations. ISC 2023: 106-124 - [i5]Oskar Taubert, Marie Weiel
Massively Parallel Genetic Optimization through Asynchronous Propagation of Populations. CoRR abs/2301.08713 (2023) - [i4]Katharina Flügel, Daniel Coquelin, Marie Weiel
Feed-Forward Optimization With Delayed Feedback for Neural Networks. CoRR abs/2304.13372 (2023) - 2022
- [j2]Daniel Coquelin
Accelerating neural network training with distributed asynchronous and selective optimization (DASO). J. Big Data 9(1): 14 (2022) - [c3]Daniel Coquelin
Hyde: The First Open-Source, Python-Based, Gpu-Accelerated Hyperspectral Denoising Package. WHISPERS 2022: 1-5 - [i3]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) - 2021
- [j1]Marie Weiel
Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions. Nat. Mach. Intell. 3(8): 727-734 (2021) - [c2]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
- [c1]Markus Götz
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics. IEEE BigData 2020: 276-287 - [i1]Markus Götz
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics. CoRR abs/2007.13552 (2020)
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