56 citations · 66 across the 10 of their papers we have counts for
11 papers
Adaptive Fluid Cohomology on Surfaces
Bastian Abt, David Stotko, Nils Wandel +1
Simulating inviscid, incompressible fluids on non-simply-connected curved surfaces requires careful treatment of the flow's local and global behavior. While recent theoretical adva…
Instant Colorization of Gaussian Splats
Daniel Lieber, Alexander Mock, Nils Wandel
Gaussian Splatting has recently become one of the most popular frameworks for photorealistic 3D scene reconstruction and rendering. While current rasterizers allow for efficient ma…
PyEvalAI: AI-assisted evaluation of Jupyter Notebooks for immediate personalized feedback
Nils Wandel, David Stotko, Alexander Schier +1
Grading student assignments in STEM courses is a laborious and repetitive task for tutors, often requiring a week to assess an entire class. For students, this delay of feedback pr…
Metamizer: a versatile neural optimizer for fast and accurate physics simulations
Nils Wandel, Stefan Schulz, Reinhard Klein
Efficient physics simulations are essential for numerous applications, ranging from realistic cloth animations or smoke effects in video games, to analyzing pollutant dispersion in…
Physics-guided Shape-from-Template: Monocular Video Perception through Neural Surrogate Models
David Stotko, Nils Wandel, Reinhard Klein
3D reconstruction of dynamic scenes is a long-standing problem in computer graphics and increasingly difficult the less information is available. Shape-from-Template (SfT) methods…
Spline-PINN: Approaching PDEs without Data using Fast, Physics-Informed Hermite-Spline CNNs
Nils Wandel, Michael Weinmann, Michael Neidlin +1
Partial Differential Equations (PDEs) are notoriously difficult to solve. In general, closed-form solutions are not available and numerical approximation schemes are computationall…
Teaching the Incompressible Navier-Stokes Equations to Fast Neural Surrogate Models in 3D
Nils Wandel, Michael Weinmann, Reinhard Klein
Physically plausible fluid simulations play an important role in modern computer graphics and engineering. However, in order to achieve real-time performance, computational speed n…
Robust Skeletonization for Plant Root Structure Reconstruction from MRI
Jannis Horn, Yi Zhao, Nils Wandel +3
Structural reconstruction of plant roots from MRI is challenging, because of low resolution and low signal-to-noise ratio of the 3D measurements which may lead to disconnectivities…
Learning Incompressible Fluid Dynamics from Scratch -- Towards Fast, Differentiable Fluid Models that Generalize
Nils Wandel, Michael Weinmann, Reinhard Klein
Fast and stable fluid simulations are an essential prerequisite for applications ranging from computer-generated imagery to computer-aided design in research and development. Howev…
3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution
Yi Zhao, Nils Wandel, Magdalena Landl +2
Magnetic resonance imaging (MRI) enables plant scientists to non-invasively study root system development and root-soil interaction. Challenging recording conditions, such as low r…
Complex Valued Gated Auto-encoder for Video Frame Prediction
Niloofar Azizi, Nils Wandel, Sven Behnke
In recent years, complex valued artificial neural networks have gained increasing interest as they allow neural networks to learn richer representations while potentially incorpora…