Search Results for author: Tassilo Kugelstadt

Found 4 papers, 0 papers with code

Wavelet-based Loss for High-frequency Interface Dynamics

no code implementations6 Sep 2022 Lukas Prantl, Jan Bender, Tassilo Kugelstadt, Nils Thuerey

As an alternative, we present a new method based on a wavelet loss formulation, which remains transparent in terms of what is optimized.

Physical Simulations Vocal Bursts Intensity Prediction

Accurately Solving Rod Dynamics with Graph Learning

no code implementations NeurIPS 2021 Han Shao, Tassilo Kugelstadt, Torsten Hädrich, Wojtek Palubicki, Jan Bender, Soeren Pirk, Dominik Michels

In this contribution, we introduce a novel method to accelerate iterative solvers for rod dynamics with graph networks (GNs) by predicting the initial guesses to reduce the number of iterations.

Graph Learning

Frequency-aware Interface Dynamics with Generative Adversarial Networks

no code implementations1 Jan 2021 Lukas Prantl, Tassilo Kugelstadt, Jan Bender, Nils Thuerey

We present a new method for reconstructing and refining complex surfaces based on physical simulations.

Physical Simulations

Accurately Solving Physical Systems with Graph Learning

no code implementations6 Jun 2020 Han Shao, Tassilo Kugelstadt, Torsten Hädrich, Wojciech Pałubicki, Jan Bender, Sören Pirk, Dominik L. Michels

In this contribution, we introduce a novel method to accelerate iterative solvers for physical systems with graph networks (GNs) by predicting the initial guesses to reduce the number of iterations.

Graph Learning

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