Ensemble Kalman Filter Optimizing Deep Neural Networks: An Alternative Approach to Non-performing Gradient Descent

Lecture notes in computer science, pp. 78–92

Authors 4

1. Alper Yegenoglu corresponding Aachen Institute of Geometry and Applied Mathematics Department of Mathematics

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · Jülich Supercomputing Centre · RWTH Aachen University

   Affiliation as printed

   Institute of Geometry and Applied Mathematics, Department of Mathematics, RWTH Aachen University, Aachen, Germany

   SimLab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany

2. Kai Krajsek

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · Jülich Supercomputing Centre

   Affiliation as printed

   SimLab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany

3. Sandra Diaz-Pier

   Forschungszentrum Jülich · Jülich Aachen Research Alliance · Jülich Supercomputing Centre

   Affiliation as printed

   SimLab Neuroscience, Jülich Supercomputing Centre (JSC), Institute for Advanced Simulation, JARA, Forschungszentrum Jülich GmbH, Jülich, Germany

4. Michaël Herty Aachen Institute of Geometry and Applied Mathematics Department of Mathematics

   RWTH Aachen University

   Affiliation as printed

   Institute of Geometry and Applied Mathematics, Department of Mathematics, RWTH Aachen University, Aachen, Germany