Nils Wandel

According to our database, Nils Wandel authored at least 10 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Metamizer: a versatile neural optimizer for fast and accurate physics simulations.

Nils Wandel, Stefan Schulz, Reinhard Klein

CoRR, 2024

Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models.

David Stotko, Nils Wandel, Reinhard Klein

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Approaching Partial Differential Equations with Physics-Driven Deep Learning

Nils Wandel

PhD thesis, 2023

2022

Spline-PINN: Approaching PDEs without Data Using Fast, Physics-Informed Hermite-Spline CNNs.

Nils Wandel, Michael Weinmann, Michael Neidlin, Reinhard Klein

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Learning Incompressible Fluid Dynamics from Scratch - Towards Fast, Differentiable Fluid Models that Generalize.

Nils Wandel, Michael Weinmann, Reinhard Klein

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Fast Fluid Simulations in 3D with Physics-Informed Deep Learning.

Nils Wandel, Michael Weinmann, Reinhard Klein

CoRR, 2020

Unsupervised Deep Learning of Incompressible Fluid Dynamics.

Nils Wandel, Michael Weinmann, Reinhard Klein

CoRR, 2020

Robust Skeletonization for Plant Root Structure Reconstruction from MRI.

Jannis Horn, Yi Zhao, Nils Wandel, Magdalena Landl, Andrea Schnepf, Sven Behnke

Proceedings of the 25th International Conference on Pattern Recognition, 2020

3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution.

Yi Zhao, Nils Wandel, Magdalena Landl, Andrea Schnepf, Sven Behnke

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

Complex Valued Gated Auto-encoder for Video Frame Prediction.

Niloofar Azizi, Nils Wandel, Sven Behnke

Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019