Solver-in-the-loop: Learning from differentiable physics to interact with iterative pde-solvers K Um, R Brand, YR Fei, P Holl, N Thuerey
Advances in Neural Information Processing Systems 33, 6111-6122, 2020
224 2020 Learning to control pdes with differentiable physics P Holl, V Koltun, N Thuerey
arXiv preprint arXiv:2001.07457, 2020
179 2020 Physics-based deep learning N Thuerey, P Holl, M Mueller, P Schnell, F Trost, K Um
arXiv preprint arXiv:2109.05237, 2021
111 2021 Holography of wi-fi radiation PM Holl, F Reinhard
Physical review letters 118 (18), 183901, 2017
80 2017 Deep learning based pulse shape discrimination for germanium detectors P Holl, L Hauertmann, B Majorovits, O Schulz, M Schuster, AJ Zsigmond
The European Physical Journal C 79, 1-9, 2019
42 2019 phiflow: A differentiable pde solving framework for deep learning via physical simulations P Holl, V Koltun, K Um, N Thuerey
NeurIPS workshop 2, 2020
39 2020 Physics-Based Deep Learning. 2021 N Thuerey, P Holl, M Mueller, P Schnell, F Trost, K Um
URL https://physicsbaseddeeplearning. org, 0
9 Half-inverse gradients for physical deep learning P Schnell, P Holl, N Thuerey
arXiv preprint arXiv:2203.10131, 2022
8 2022 Learning to control pdes with differentiable physics (2020) P Holl, V Koltun, N Thuerey
arXiv preprint arXiv:2001.07457, 2001
7 2001 Scale-invariant learning by physics inversion P Holl, V Koltun, N Thuerey
Advances in Neural Information Processing Systems 35, 5390-5403, 2022
5 2022 Simulating liquids with graph networks J Klimesch, P Holl, N Thuerey
arXiv preprint arXiv:2203.07895, 2022
4 2022 Physical gradients for deep learning P Holl, N Thuerey, V Koltun
3 2021 : Intuitive Scientific Computing with Dimension Types for Jax, PyTorch, TensorFlow & NumPyP Holl, N Thuerey
Journal of Open Source Software 9 (95), 6171, 2024
2024 Learning Time-Aware Assistance Functions for Numerical Fluid Solvers K Um, YR Fei, P Holl, N Thuerey
2020 Can Neural Networks Improve Classical Optimization of Inverse Problems? P Holl, N Thuerey
Differentiable Physics for Improving the Accuracy of Iterative PDE-Solvers with Neural Networks K Um, YR Fei, P Holl, R Brand, N Thuerey