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phiflow: A Differentiable PDE Solving Framework for Deep Learning via Physical Simulations

Philipp Holl 1 Vladlen Koltun 2 Kiwon Um 3, 4, 5 Nils Thuerey 1 
1 TUM - Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne]
2 INTEL LABS - INTEL Labs
3 IP Paris - Institut Polytechnique de Paris
4 IDS - Département Images, Données, Signal
5 IMAGES - Image, Modélisation, Analyse, GEométrie, Synthèse
LTCI - Laboratoire Traitement et Communication de l'Information
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https://hal.telecom-paris.fr/hal-03142278
Contributor : Kiwon UM Connect in order to contact the contributor
Submitted on : Monday, February 15, 2021 - 10:33:59 PM
Last modification on : Thursday, January 6, 2022 - 11:38:05 AM

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  • HAL Id : hal-03142278, version 1

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INSTITUT-TELECOM | LTCI | IDS | IMAGES | IP_PARIS

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Philipp Holl, Vladlen Koltun, Kiwon Um, Nils Thuerey. phiflow: A Differentiable PDE Solving Framework for Deep Learning via Physical Simulations. NeurIPS Workshop, 2020. ⟨hal-03142278⟩

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