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
271 2020 Learning to control pdes with differentiable physics P Holl, V Koltun, N Thuerey
arXiv preprint arXiv:2001.07457, 2020
215 2020 Physics-based deep learning N Thuerey, P Holl, M Mueller, P Schnell, F Trost, K Um
arXiv preprint arXiv:2109.05237, 2021
143 2021 Holography of wi-fi radiation PM Holl, F Reinhard
Physical review letters 118 (18), 183901, 2017
87 2017 phiflow: A differentiable pde solving framework for deep learning via physical simulations P Holl, V Koltun, K Um, N Thuerey
NeurIPS workshop 2, 2020
60 2020 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
45 2019 Physics-Based Deep Learning. 2021 N Thuerey, P Holl, M Mueller, P Schnell, F Trost, K Um
URL https://physicsbaseddeeplearning. org, 0
14 Half-inverse gradients for physical deep learning P Schnell, P Holl, N Thuerey
arXiv preprint arXiv:2203.10131, 2022
10 2022 Simulating liquids with graph networks J Klimesch, P Holl, N Thuerey
arXiv preprint arXiv:2203.07895, 2022
9 2022 Scale-invariant learning by physics inversion P Holl, V Koltun, N Thuerey
Advances in Neural Information Processing Systems 35, 5390-5403, 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 P Holl, N Thuerey
Forty-first International Conference on Machine Learning, 0
4 Φ-ML: Intuitive Scientific Computing with Dimension Types for Jax, PyTorch, TensorFlow & NumPy P Holl, N Thuerey
Journal of Open Source Software 9 (95), 6171, 2024
3 2024 Physical gradients for deep learning P Holl, N Thuerey, V Koltun
3 2021 The Unreasonable Effectiveness of Solving Inverse Problems with Neural Networks P Holl, N Thuerey
arXiv preprint arXiv:2408.08119, 2024
2024 P Holl, N Thuerey
ICML 2024 Workshop on Differentiable Almost Everything: Differentiable …, 0
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
Learning Time-Aware Assistance Functions for Numerical Fluid Solvers K Um, YR Fei, P Holl, N Thuerey
