| Sampling from Boltzmann densities with physics informed low-rank formats P Hagemann, J Schütte, D Sommer, M Eigel, G Steidl arXiv preprint arXiv:2412.07637, 2024 | 1 | 2024 |
| Adaptive Multilevel Neural Networks for Parametric PDEs with Error Estimation JE Schütte, M Eigel ICLR 2024 Workshop on AI4DifferentialEquations In Science, 2024 | 1 | 2024 |
| Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures C Miranda, J Schütte, D Sommer, M Eigel arXiv preprint arXiv:2311.03242, 2023 | 1 | 2023 |
| Multilevel CNNs for parametric pdes based on adaptive finite elements JE Schütte, M Eigel arXiv preprint arXiv:2408.10838, 2024 | | 2024 |
| Mini-Workshop: Nonlinear Approximation of High-dimensional Functions in Scientific Computing M Oster, J Schütte, P Trunschke Oberwolfach Reports 20 (4), 2771-2808, 2024 | | 2024 |
| Solving Parametric PDEs with Neural Networks M Eigel, J Schütte Annual Research Report 2023, 2023 | | 2023 |
Martin EigelWeierstrass Institute for Applied Analysis and Stochastics BerlinEmail verificata su wias-berlin.de