2 citations · 3 across the 6 of their papers we have counts for
6 papers
An Exponential Averaging Process with Strong Convergence Properties
Frederik Köhne, Anton Schiela
Averaging, or smoothing, is a fundamental approach to obtain stable, de-noised estimates from noisy observations. In certain scenarios, observations made along trajectories of rand…
Nonlinear Fenchel Conjugates
Anton Schiela, Roland Herzog, Ronny Bergmann
The classical concept of Fenchel conjugation is tailored to extended real-valued functions defined on linear spaces. In this paper we generalize this concept to functions defined o…
-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…
Frobenius-Type Norms and Inner Products of Matrices and Linear Maps with Applications to Neural Network Training
Roland Herzog, Frederik Köhne, Leonie Kreis +1
The Frobenius norm is a frequent choice of norm for matrices. In particular, the underlying Frobenius inner product is typically used to evaluate the gradient of an objective with…
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…