| Dynamic particle swarm optimization of biomolecular simulation parameters with flexible objective functions M Weiel, M Götz, A Klein, D Coquelin, R Floca, A Schug Nature machine intelligence 3 (8), 727-734, 2021 | 28 | 2021 |
| HeAT–a Distributed and GPU-accelerated Tensor Framework for Data Analytics M Götz, C Debus, D Coquelin, K Krajsek, C Comito, P Knechtges, ... 2020 IEEE International Conference on Big Data (Big Data), 276-287, 2020 | 12 | 2020 |
| HyDe: The first open-source, Python-based, GPU-accelerated hyperspectral denoising package D Coquelin, B Rasti, M Götz, P Ghamisi, R Gloaguen, A Streit 2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution …, 2022 | 6 | 2022 |
| Accelerating neural network training with distributed asynchronous and selective optimization (DASO) D Coquelin, C Debus, M Götz, F von der Lehr, J Kahn, M Siggel, A Streit Journal of Big Data 9 (1), 14, 2022 | 6 | 2022 |
| Evolutionary optimization of neural architectures in remote sensing classification problems D Coquelin, R Sedona, M Riedel, M Götz 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 1587 …, 2021 | 6 | 2021 |
| Feed-forward optimization with delayed feedback for neural networks K Flügel, D Coquelin, M Weiel, C Debus, A Streit, M Götz arXiv preprint arXiv:2304.13372, 2023 | 4 | 2023 |
| Massively parallel genetic optimization through asynchronous propagation of populations O Taubert, M Weiel, D Coquelin, A Farshian, C Debus, A Schug, A Streit, ... International Conference on High Performance Computing, 106-124, 2023 | 3 | 2023 |
| RNA contact prediction by data efficient deep learning O Taubert, F von der Lehr, A Bazarova, C Faber, P Knechtges, M Weiel, ... Communications Biology 6 (1), 913, 2023 | 1 | 2023 |
| Harnessing Orthogonality to Train Low-Rank Neural Networks D Coquelin, K Flügel, M Weiel, N Kiefer, C Debus, A Streit, M Götz arXiv preprint arXiv:2401.08505, 2024 | | 2024 |
| Check for updates Massively Parallel Genetic Optimization Through Asynchronous Propagation of Populations O Taubert, M Weiel, D Coquelin, A Farshian, C Debus, A Schug, A Streit High Performance Computing: 38th International Conference, ISC High …, 2023 | | 2023 |
| helmholtz-analytics/heat: Scalable SVD, GSoC22 contributions, Docker image, PyTorch 2 support, AMD GPUs acceleration (v1. 3.0) C Comito, P Shah, SH Neo, M Siggel, D Coquelin, B Hagemeier, ... Jülich Supercomputing Center, 2023 | | 2023 |
| HeAT: a High-Performance-Computing Library for Scientific Big Data Analytics C Comito, D Coquelin, C Debus, M Götz, B Hagemeier, S Hanselmann, ... Astronomical Data Analysis Software and Systems XXIX 527, 191, 2020 | | 2020 |
| Practical considerations in modeling the low light response of photomultiplier tubes in large batch testing D Coquelin, T Jobin, W Kemmerer, P Maxwell, S Merten, E Moller, ... Nuclear Instruments and Methods in Physics Research Section A: Accelerators …, 2019 | | 2019 |
| A 65 nm pixel readout chip in 65 nm process with passive CMOS sensor D Coquelin, M Daas, T Hemperek, F Hügging, H Krüger, DL Pohl, ... Verhandlungen der Deutschen Physikalischen Gesellschaft, 2018 | | 2018 |
