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Efficient and Modular Implicit Differentiation


May 31, 2021
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert


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Variational Data Assimilation with a Learned Inverse Observation Operator


Feb 22, 2021
Thomas Frerix, Dmitrii Kochkov, Jamie A. Smith, Daniel Cremers, Michael P. Brenner, Stephan Hoyer


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Machine learning accelerated computational fluid dynamics


Jan 28, 2021
Dmitrii Kochkov, Jamie A. Smith, Ayya Alieva, Qing Wang, Michael P. Brenner, Stephan Hoyer

* 13 pages, 9 figures 

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Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics


Sep 17, 2020
Li Li, Stephan Hoyer, Ryan Pederson, Ruoxi Sun, Ekin D. Cubuk, Patrick Riley, Kieron Burke


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Lagrangian Neural Networks


Mar 10, 2020
Miles Cranmer, Sam Greydanus, Stephan Hoyer, Peter Battaglia, David Spergel, Shirley Ho

* 7 pages (+2 appendix). Accepted to ICLR 2020 Deep Differential Equations Workshop. Code at github.com/MilesCranmer/lagrangian_nns 

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Inundation Modeling in Data Scarce Regions


Oct 30, 2019
Zvika Ben-Haim, Vladimir Anisimov, Aaron Yonas, Varun Gulshan, Yusef Shafi, Stephan Hoyer, Sella Nevo

* To appear in the Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop (AI+HADR) @ NeurIPS 2019 

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Neural reparameterization improves structural optimization


Sep 14, 2019
Stephan Hoyer, Jascha Sohl-Dickstein, Sam Greydanus


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Data-driven metasurface discovery


Nov 29, 2018
Jiaqi Jiang, David Sell, Stephan Hoyer, Jason Hickey, Jianji Yang, Jonathan A. Fan

* 14 pages, 5 figures 

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Correcting Nuisance Variation using Wasserstein Distance


Nov 02, 2017
Gil Tabak, Minjie Fan, Samuel J. Yang, Stephan Hoyer, Geoff Davis

* 11 pages, 5 figures 

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The Cramer Distance as a Solution to Biased Wasserstein Gradients


May 30, 2017
Marc G. Bellemare, Ivo Danihelka, Will Dabney, Shakir Mohamed, Balaji Lakshminarayanan, Stephan Hoyer, Rémi Munos


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