Stephan Hoyer

According to our database, Stephan Hoyer authored at least 21 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Accelerating scientific discovery with the common task framework.

J. Nathan Kutz, Peter W. Battaglia, Michael P. Brenner, Kevin Carlberg, Aric A. Hagberg, Shirley Ho, Stephan Hoyer, Henning Lange, Hod Lipson, Michael W. Mahoney, Frank Noé, Max Welling, Laure Zanna, Francis Zhu, Steven L. Brunton

CoRR, November, 2025

2024

Neural general circulation models for weather and climate.

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

Nat., August, 2024

Neural general circulation models optimized to predict satellite-based precipitation observations.

Janni Yuval, Ian Langmore, Dmitrii Kochkov, Stephan Hoyer

CoRR, 2024

4D-Var using Hessian approximation and backpropagation applied to automatically-differentiable numerical and machine learning models.

Kylen Solvik, Stephen G. Penny, Stephan Hoyer

CoRR, 2024

DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems.

Yair Schiff, Zhong Yi Wan, Jeffrey B. Parker, Stephan Hoyer, Volodymyr Kuleshov, Fei Sha, Leonardo Zepeda-Núñez

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Learning to correct spectral methods for simulating turbulent flows.

Gideon Dresdner, Dmitrii Kochkov, Peter Christian Norgaard, Leonardo Zepeda-Núñez, Jamie A. Smith, Michael P. Brenner, Stephan Hoyer

Trans. Mach. Learn. Res., 2023

Neural General Circulation Models.

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

CoRR, 2023

WeatherBench 2: A benchmark for the next generation of data-driven global weather models.

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

CoRR, 2023

Python Array API Standard: Toward Array Interoperability in the Scientific Python Ecosystem.

Aaron Meurer, Athan Reines, Ralf Gommers, Yao-Lung L. Fang, John Kirkham, Matthew Barber, Stephan Hoyer, Andreas Müller, Sheng Zha, Saul Shanabrook, Stephannie Jiménez Gacha, Mario Lezcano Casado, Thomas J. Fan, Tyler Reddy, Alexandre Passos, Hyukjin Kwon, Travis E. Oliphant, Consortium for Python Data API Standards

Proceedings of the 22nd Python in Science Conference, 2023

2022

GraphCast: Learning skillful medium-range global weather forecasting.

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

CoRR, 2022

Efficient and Modular Implicit Differentiation.

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Machine learning accelerated computational fluid dynamics.

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

CoRR, 2021

Variational Data Assimilation with a Learned Inverse Observation Operator.

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

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Array programming with NumPy.

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

Nat., 2020

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

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

CoRR, 2020

Lagrangian Neural Networks.

Miles D. Cranmer, Sam Greydanus, Stephan Hoyer, Peter W. Battaglia, David N. Spergel, Shirley Ho

CoRR, 2020

2019

Inundation Modeling in Data Scarce Regions.

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

CoRR, 2019

Neural reparameterization improves structural optimization.

Stephan Hoyer, Jascha Sohl-Dickstein, Sam Greydanus

CoRR, 2019

2018

Data-driven metasurface discovery.

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

CoRR, 2018

Assessing microscope image focus quality with deep learning.

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

BMC Bioinform., 2018

2017

The Cramer Distance as a Solution to Biased Wasserstein Gradients.

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

CoRR, 2017