This title appears in the Scientific Report :
2020
Ensemble Kalman Filter optimizing Deep Neural Networks: An alternative approach to non-performing Gradient Descent
Ensemble Kalman Filter optimizing Deep Neural Networks: An alternative approach to non-performing Gradient Descent
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Personal Name(s): | Yegenoglu, Alper (Corresponding author) |
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Diaz, Sandra / Krajsek, Kai / Herty, Michael | |
Contributing Institute: |
Jülich Supercomputing Center; JSC |
Imprint: |
2020
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Conference: | The Sixth International Conference on Machine Learning, Optimization, and Data Science, Siena (Italy), 2020-07-19 - 2020-07-22 |
Document Type: |
Conference Presentation |
Research Program: |
Helmholtz School for Data Science in Life, Earth and Energy (HDS LEE) SimLab Neuroscience Center for Simulation and Data Science (CSD) - School for Simulation and Data Science (SSD) Supercomputing and Modelling for the Human Brain Computational Science and Mathematical Methods Helmholtz Analytics Framework Doktorand ohne besondere Förderung |
Publikationsportal JuSER |
Description not available. |