Daniel Coquelin

17 papers A 1B 1C 2Journal 10Unranked 3
YearRankTypeTitle / Venue / Authors
2025 B conf
Beyond Backpropagation: Optimization with Multi-Tangent Forward Gradients.
IJCNN
Katharina Flügel, Daniel Coquelin, Marie Weiel, Charlotte Debus, Achim Streit, Markus Götz
2024 J jnl
AB-Training: A Communication-Efficient Approach for Distributed Low-Rank Learning.
CoRR
Daniel Coquelin, Katherina Flügel, Marie Weiel, Nicholas Kiefer, Muhammed Öz, Charlotte Debus, Achim Streit, Markus Götz
2024 J jnl
Beyond Backpropagation: Optimization with Multi-Tangent Forward Gradients.
CoRR
Katharina Flügel, Daniel Coquelin, Marie Weiel, Achim Streit, Markus Götz
2024 — conf
Feed-Forward Optimization With Delayed Feedback for Neural Network Training.
ICONIP (4)
Katharina Flügel, Daniel Coquelin, Marie Weiel, Charlotte Debus, Achim Streit, Markus Götz
2024 A conf
Harnessing Orthogonality to Train Low-Rank Neural Networks.
ECAI
Daniel Coquelin, Katharina Flügel, Marie Weiel, Nicholas Kiefer, Charlotte Debus, Achim Streit, Markus Götz
2024 J jnl
Harnessing Orthogonality to Train Low-Rank Neural Networks.
CoRR
Daniel Coquelin, Katharina Flügel, Marie Weiel, Nicholas Kiefer, Charlotte Debus, Achim Streit, Markus Götz
2023 J jnl
Feed-Forward Optimization With Delayed Feedback for Neural Networks.
CoRR
Katharina Flügel, Daniel Coquelin, Marie Weiel, Charlotte Debus, Achim Streit, Markus Götz
2023 C conf
Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations.
ISC
Oskar Taubert, Marie Weiel, Daniel Coquelin, Anis Farshian, Charlotte Debus, Alexander Schug, Achim Streit, Markus Götz
2023 J jnl
Massively Parallel Genetic Optimization through Asynchronous Propagation of Populations.
CoRR
Oskar Taubert, Marie Weiel, Daniel Coquelin, Anis Farshian, Charlotte Debus, Alexander Schug, Achim Streit, Markus Götz
2022 J jnl
Accelerating neural network training with distributed asynchronous and selective optimization (DASO).
J. Big Data
Daniel Coquelin, Charlotte Debus, Markus Götz, Fabrice von der Lehr, James Kahn, Martin Siggel, Achim Streit
2022 J jnl
HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising Package.
CoRR
Daniel Coquelin, Behnood Rasti, Markus Götz, Pedram Ghamisi, Richard Gloaguen, Achim Streit
2022 — conf
Hyde: The First Open-Source, Python-Based, Gpu-Accelerated Hyperspectral Denoising Package.
WHISPERS
Daniel Coquelin, Behnood Rasti, Markus Götz, Pedram Ghamisi, Richard Gloaguen, Achim Streit
2021 J jnl
Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO).
CoRR
Daniel Coquelin, Charlotte Debus, Markus Götz, Fabrice von der Lehr, James Kahn, Martin Siggel, Achim Streit
2021 J jnl
Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions.
Nat. Mach. Intell.
Marie Weiel, Markus Götz, André Klein, Daniel Coquelin, Ralf Floca, Alexander Schug
2021 C conf
Evolutionary Optimization of Neural Architectures in Remote Sensing Classification Problems.
IGARSS
Daniel Coquelin, Rocco Sedona, Morris Riedel, Markus Götz
2020 — conf
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics.
IEEE BigData
Markus Götz, Charlotte Debus, Daniel Coquelin, Kai Krajsek, Claudia Comito, Philipp Knechtges, Björn Hagemeier, Michael Tarnawa, Simon Hanselmann, Martin Siggel, Achim Basermann, Achim Streit
2020 J jnl
HeAT - a Distributed and GPU-accelerated Tensor Framework for Data Analytics.
CoRR
Markus Götz, Daniel Coquelin, Charlotte Debus, Kai Krajsek, Claudia Comito, Philipp Knechtges, Björn Hagemeier, Michael Tarnawa, Simon Hanselmann, Martin Siggel, Achim Basermann, Achim Streit