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2020 – today
- 2024
[j4]Dmitrii Kochkov
, Janni Yuval, Ian Langmore, Peter C. Norgaard, Jamie A. Smith, Griffin Mooers, Milan Klöwer, James Lottes, Stephan Rasp, Peter D. Düben, Sam Hatfield, Peter W. Battaglia, Alvaro Sanchez-Gonzalez, Matthew Willson, Michael P. Brenner, Stephan Hoyer:
Neural general circulation models for weather and climate. Nat. 632(8027): 1060-1066 (2024)- [c3]Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez:
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. ICML 2024 - [i16]Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez:
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems. CoRR abs/2402.04467 (2024) - [i15]Kylen Solvik, Stephen G. Penny, Stephan Hoyer:
4D-Var using Hessian approximation and backpropagation applied to automatically-differentiable numerical and machine learning models. CoRR abs/2408.02767 (2024) - 2023
- [j3]Gideon Dresdner, Dmitrii Kochkov, Peter Christian Norgaard, Leonardo Zepeda-Núñez, Jamie A. Smith, Michael P. Brenner, Stephan Hoyer:
Learning to correct spectral methods for simulating turbulent flows. Trans. Mach. Learn. Res. 2023 (2023) - [i14]Stephan Rasp, Stephan Hoyer, Alexander Merose, Ian Langmore, Peter W. Battaglia, Tyler Russell, Alvaro Sanchez-Gonzalez, Vivian Yang, Rob Carver, Shreya Agrawal, Matthew Chantry, Zied Ben Bouallegue, Peter Dueben, Carla Bromberg, Jared Sisk, Luke Barrington, Aaron Bell, Fei Sha:
WeatherBench 2: A benchmark for the next generation of data-driven global weather models. CoRR abs/2308.15560 (2023) - [i13]Dmitrii Kochkov, Janni Yuval, Ian Langmore, Peter C. Norgaard, Jamie A. Smith, Griffin Mooers, James Lottes, Stephan Rasp, Peter D. Düben, Milan Klöwer, Sam Hatfield, Peter W. Battaglia, Alvaro Sanchez-Gonzalez, Matthew Willson, Michael P. Brenner, Stephan Hoyer:
Neural General Circulation Models. CoRR abs/2311.07222 (2023) - 2022
- [c2]Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert:
Efficient and Modular Implicit Differentiation. NeurIPS 2022 - [i12]Gideon Dresdner, Dmitrii Kochkov, Peter C. Norgaard, Leonardo Zepeda-Núñez, Jamie A. Smith, Michael P. Brenner, Stephan Hoyer:
Learning to correct spectral methods for simulating turbulent flows. CoRR abs/2207.00556 (2022) - [i11]Rémi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Alexander Pritzel, Suman V. Ravuri, Timo Ewalds, Ferran Alet, Zach Eaton-Rosen, Weihua Hu, Alexander Merose, Stephan Hoyer, George Holland, Jacklynn Stott, Oriol Vinyals, Shakir Mohamed, Peter W. Battaglia:
GraphCast: Learning skillful medium-range global weather forecasting. CoRR abs/2212.12794 (2022) - 2021
- [c1]Thomas Frerix, Dmitrii Kochkov, Jamie A. Smith, Daniel Cremers, Michael P. Brenner, Stephan Hoyer:
Variational Data Assimilation with a Learned Inverse Observation Operator. ICML 2021: 3449-3458 - [i10]Dmitrii Kochkov, Jamie A. Smith, Ayya Alieva, Qing Wang, Michael P. Brenner, Stephan Hoyer:
Machine learning accelerated computational fluid dynamics. CoRR abs/2102.01010 (2021) - [i9]Thomas Frerix, Dmitrii Kochkov, Jamie A. Smith, Daniel Cremers, Michael P. Brenner, Stephan Hoyer:
Variational Data Assimilation with a Learned Inverse Observation Operator. CoRR abs/2102.11192 (2021) - [i8]Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert:
Efficient and Modular Implicit Differentiation. CoRR abs/2105.15183 (2021) - 2020
- [j2]Charles R. Harris, K. Jarrod Millman, Stéfan van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, Robert Kern, Matti Picus, Stephan Hoyer, Marten H. van Kerkwijk, Matthew Brett, Allan Haldane, Jaime Fernández del Río, Mark Wiebe, Pearu Peterson, Pierre Gérard-Marchant, Kevin Sheppard, Tyler Reddy, Warren Weckesser, Hameer Abbasi, Christoph Gohlke, Travis E. Oliphant:
Array programming with NumPy. Nat. 585: 357-362 (2020) - [i7]Miles D. Cranmer, Sam Greydanus, Stephan Hoyer, Peter W. Battaglia, David N. Spergel, Shirley Ho:
Lagrangian Neural Networks. CoRR abs/2003.04630 (2020) - [i6]Charles R. Harris, K. Jarrod Millman, Stéfan van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, Robert Kern, Matti Picus, Stephan Hoyer, Marten H. van Kerkwijk, Matthew Brett, Allan Haldane, Jaime Fernández del Río, Mark Wiebe, Pearu Peterson, Pierre Gérard-Marchant, Kevin Sheppard, Tyler Reddy, Warren Weckesser, Hameer Abbasi, Christoph Gohlke, Travis E. Oliphant:
Array Programming with NumPy. CoRR abs/2006.10256 (2020) - [i5]Li Li, Stephan Hoyer, Ryan Pederson, Ruoxi Sun, Ekin D. Cubuk, Patrick Riley, Kieron Burke:
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics. CoRR abs/2009.08551 (2020)
2010 – 2019
- 2019
- [i4]Stephan Hoyer, Jascha Sohl-Dickstein, Sam Greydanus:
Neural reparameterization improves structural optimization. CoRR abs/1909.04240 (2019) - [i3]Zvika Ben-Haim, Vladimir Anisimov, Aaron Yonas, Varun Gulshan, Yusef Shafi, Stephan Hoyer, Sella Nevo:
Inundation Modeling in Data Scarce Regions. CoRR abs/1910.05006 (2019) - 2018
- [j1]Samuel J. Yang, Marc Berndl, D. Michael Ando, Mariya Barch, Arunachalam Narayanaswamy, Eric Christiansen, Stephan Hoyer, Chris Roat, Jane Hung, Curtis T. Rueden, Asim Shankar, Steven Finkbeiner, Philip Nelson:
Assessing microscope image focus quality with deep learning. BMC Bioinform. 19(1): 77:1-77:9 (2018) - [i2]Jiaqi Jiang, David Sell, Stephan Hoyer, Jason Hickey, Jianji Yang, Jonathan A. Fan:
Data-driven metasurface discovery. CoRR abs/1811.12436 (2018) - 2017
- [i1]Marc G. Bellemare, Ivo Danihelka, Will Dabney, Shakir Mohamed, Balaji Lakshminarayanan, Stephan Hoyer, Rémi Munos:
The Cramer Distance as a Solution to Biased Wasserstein Gradients. CoRR abs/1705.10743 (2017)
Coauthor Index
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