130 citations · 216 across the 7 of their papers we have counts for
4 papers · 1 filter
ScalarFlow: A Large-Scale Volumetric Data Set of Real-world Scalar Transport Flows for Computer Animation and Machine Learning
Marie-Lena Eckert, Kiwon Um, Nils Thuerey
In this paper, we present ScalarFlow, a first large-scale data set of reconstructions of real-world smoke plumes. We additionally propose a framework for accurate physics-based rec…
Perceptual Evaluation of Liquid Simulation Methods
Kiwon Um, Xiangyu Hu, Nils Thuerey
This paper proposes a novel framework to evaluate fluid simulation methods based on crowd-sourced user studies in order to robustly gather large numbers of opinions. The key idea f…
Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solvers
Kiwon Um, Robert Brand, Yun +3
Finding accurate solutions to partial differential equations (PDEs) is a crucial task in all scientific and engineering disciplines. It has recently been shown that machine learnin…
Learning Similarity Metrics for Numerical Simulations
Georg Kohl, Kiwon Um, Nils Thuerey
We propose a neural network-based approach that computes a stable and generalizing metric (LSiM) to compare data from a variety of numerical simulation sources. We focus on scalar…