Papers matching “deep neural network training” 521
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Neural network training under semidefinite constraints2022 Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes conference-paper Computer Science Stochastic Gradient Optimization Techniques cited by 1 patent
Patricia Pauli, Niklas Funcke, Dennis Gramlich, Mohamed Amine Msalmi, Frank Allgöwer
10citations -
Smaller generalization error derived for a deep residual neural network compared with shallow networks2022 IMA Journal of Numerical Analysis article Computer Science Stochastic Gradient Optimization Techniques Open access
Aku Kammonen, Jonas Kiessling, Petr Plecháč, Mattias Sandberg, Anders Szepessy, Raul F. Tempone
4citations -
Identification of Martensite Bands in Dual‐Phase Steels: A Deep Learning Object Detection Approach Using Faster Region‐Based‐Convolutional Neural Network2023 steel research international article Engineering Microstructure and Mechanical Properties of Steels Open access
Niklas C. Fehlemann, Ana Lia Suarez Aguilera, Stefan Sandfeld, Maximilian Neite, David Lenz, Markus Könemann, +1 more
9citations -
Introducing a Deep Neural Network-Based Model Predictive Control Framework for Rapid Controller Implementation2024 Proceedings of the ... American Control Conference/Proceedings of the American Control Conference conference-paper Engineering Advanced Control Systems Optimization Open access
Alexander Winkler, Julian Bedei, Patrick Schaber, Stefan Pischinger, Jakob Andert, Charles Robert Koch
14citations -
Using Synthesized IMU Data to Train a Long-Short Term Memory-based Neural Network for Unobtrusive Gait Analysis with a Sparse Sensor Setup6citations
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Newton versus the machine: solving the chaotic three-body problem using deep neural networks2020 Monthly Notices of the Royal Astronomical Society article Physics and Astronomy Model Reduction and Neural Networks Open access cited by 1 patent
Philip G. Breen, Christopher N. Foley, Tjarda Boekholt, Simon Portegies Zwart
97citations -
DNN2: A hyper-parameter reinforcement learning game for self-design of neural network based elasto-plastic constitutive descriptions2021 Computers & Structures article Materials Science Machine Learning in Materials Science Open access
Alexander Fuchs, Yousef Heider, Kun Wang, WaiChing Sun, Michael Kaliske
58citations -
Ensemble Kalman Filter Optimizing Deep Neural Networks: An Alternative Approach to Non-performing Gradient Descent2020 Lecture notes in computer science conference-paper Computer Science Stochastic Gradient Optimization Techniques
Alper Yegenoglu, Kai Krajsek, Sandra Diaz-Pier, Michaël Herty
7citations -
Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers2021 Information and Inference A Journal of the IMA article Computer Science Stochastic Gradient Optimization Techniques Open access
Bubacarr Bah, Holger Rauhut, Ulrich Terstiege, Michael Westdickenberg
29citations -
Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples2021 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access
Christian Fiedler, Massimo Fornasier, Timo Klock, Michael Rauchensteiner
0citations