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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
5
IMAGES - Image, Modélisation, Analyse, GEométrie, Synthèse
LTCI - Laboratoire Traitement et Communication de l'Information
1
TUM - Technical University of Munich (Arcisstrasse 21, D- 80333 München - Germany)
3
IP Paris - Institut Polytechnique de Paris (France)
4
IDS - Département Images, Données, Signal (46, rue Barrault
75013 Paris - France)
- Télécom ParisTech (46 rue Barrault 75634 Paris Cedex 13 - France)
5
IMAGES - Image, Modélisation, Analyse, GEométrie, Synthèse (46 rue Barrault
75013 Paris - France)
- LTCI - Laboratoire Traitement et Communication de l'Information (19 Place Marguerite Perey 91120 PALAISEAU - France)
- IMT - Institut Mines-Télécom [Paris] (37-39 Rue Dareau, 75014 Paris - France)
- Télécom Paris (19 Place Marguerite Perey 91120 Palaiseau - France)
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Other publications
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https://hal.telecom-paris.fr/hal-03142278
Contributor : Kiwon Um <>
Submitted on : Monday, February 15, 2021 - 10:33:59 PM
Last modification on : Wednesday, February 17, 2021 - 3:31:14 AM
Contributor : Kiwon Um <>
Submitted on : Monday, February 15, 2021 - 10:33:59 PM
Last modification on : Wednesday, February 17, 2021 - 3:31:14 AM
Identifiers
- HAL Id : hal-03142278, version 1
Collections
INSTITUT-TELECOM | IP_PARIS | IDS | IMAGES | LTCI
Citation
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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