2 citations · 2 across the 4 of their papers we have counts for
4 papers
-error bounds for approximations of the Koopman operator by kernel extended dynamic mode decomposition
Frederik Köhne, Friedrich M. Philipp, Manuel Schaller +2
Extended dynamic mode decomposition (EDMD) is a well-established method to generate a data-driven approximation of the Koopman operator for analysis and prediction of nonlinear dyn…
Adaptive Step Sizes for Preconditioned Stochastic Gradient Descent
Frederik Köhne, Leonie Kreis, Anton Schiela +1
This paper proposes a novel approach to adaptive step sizes in stochastic gradient descent (SGD) by utilizing quantities that we have identified as numerically traceable -- the Lip…
SensLI: Sensitivity-Based Layer Insertion for Neural Networks
Leonie Kreis, Evelyn Herberg, Frederik Köhne +2
The training of neural networks requires tedious and often manual tuning of the network architecture. We propose a systematic approach to inserting new layers during the training p…
Time Regularization in Optimal Time Variable Learning
Evelyn Herberg, Roland Herzog, Frederik Köhne
Recently, optimal time variable learning in deep neural networks (DNNs) was introduced in arXiv:2204.08528. In this manuscript we extend the concept by introducing a regularization…