Error bounds for approximations with deep ReLU neural networks in norms I Gühring, G Kutyniok, P Petersen Analysis and Applications 18 (05), 803-859, 2020 | 199 | 2020 |
Approximation rates for neural networks with encodable weights in smoothness spaces I Gühring, M Raslan Neural Networks 134, 107-130, 2020 | 86 | 2020 |
Expressivity of deep neural networks I Gühring, M Raslan, G Kutyniok arXiv preprint arXiv:2007.04759, 2020 | 64 | 2020 |
Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning M Genzel, I Gühring, J Macdonald, M März International Conference on Machine Learning (ICML), 2022 | 25 | 2022 |
A neural multilevel method for high-dimensional parametric PDEs C Heiß, I Gühring, M Eigel NeurIPS workshop on The Symbiosis of Deep Learning and Differential …, 2021 | 7 | 2021 |
Multilevel CNNs for Parametric PDEs C Heiß, I Gühring, M Eigel Journal of Machine Learning Research 24 (373), 1--42, 2023 | 5 | 2023 |
Approximation with Neural Networks from a Theoretical and Practical Perspective I Gühring TU Berlin, Institut für Softwaretechnik und Theoretische Informatik, 2022 | | 2022 |
Near-Exact Recovery for Sparse-View CT via Data-Driven Methods M Genzel, I Gühring, J Macdonald, M Maximilian NeurIPS workshop on Deep Learning and Inverse Problems, 2021 | | 2021 |
Eigenvalues in gaps of G-selfadjoint operators in Almost Pontryagin spaces I Gühring Technische Universität Berlin, 2017 | | 2017 |