Maximal discrete sparsity in parabolic optimal control with measures E Herberg, M Hinze, H Schumacher Mathematical Control and Related Fields 10 (4), 735-759, 2020 | 9 | 2020 |
An Optimal Time Variable Learning Framework for Deep Neural Networks H Antil, H Díaz, E Herberg Annals of Mathematical Sciences and Applications 8 (3), 501-543, 2023 | 6 | 2023 |
Variational discretization approach applied to an optimal control problem with bounded measure controls E Herberg, M Hinze Optimization and Control for Partial Differential Equations: Uncertainty …, 2022 | 5 | 2022 |
Sparse discretization of sparse control problems with measures E Herberg | 3 | 2021 |
An inexact semismooth newton method with application to adaptive randomized sketching for dynamic optimization M Alshehri, H Antil, E Herberg, DP Kouri Finite Elements in Analysis and Design 228, 2024 | 2 | 2024 |
Lecture Notes: Neural Network Architectures E Herberg arXiv preprint arXiv:2304.05133, 2023 | 2 | 2023 |
Variational discretization of one-dimensional elliptic optimal control problems with BV functions based on the mixed formulation E Herberg, M Hinze Mathematical Control and Related Fields 13 (2), 695-720, 2023 | 1 | 2023 |
Time regularization in optimal time variable learning E Herberg, R Herzog, F Köhne PAMM 24 (1), e202300299, 2024 | | 2024 |
Sensitivity-Based Layer Insertion for Residual and Feedforward Neural Networks E Herberg, R Herzog, F Köhne, L Kreis, A Schiela arXiv preprint arXiv:2311.15995, 2023 | | 2023 |
Variationelle Diskretisierung für Optimale Steuerung mit Maßkontrollen E Herberg Mitteilungen der Deutschen Mathematiker-Vereinigung 31 (3), 156-159, 2023 | | 2023 |
Adaptive Randomized Sketching for Dynamic Nonsmooth Optimization RJ Baraldi, E Herberg, DP Kouri, H Antil Model Validation and Uncertainty Quantification 3, 107-116, 2023 | | 2023 |
Sparse discretization of sparse control problems E Herberg, M Hinze, H Schumacher PAMM 19 (1), e201900105, 2019 | | 2019 |