Stephan Hoyer

Orcid: 0000-0002-5207-0380

According to our database1, Stephan Hoyer authored at least 18 papers between 2017 and 2024.

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Bibliography

2024
Neural general circulation models for weather and climate.
Nat., August, 2024

4D-Var using Hessian approximation and backpropagation applied to automatically-differentiable numerical and machine learning models.
CoRR, 2024

DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Learning to correct spectral methods for simulating turbulent flows.
Trans. Mach. Learn. Res., 2023

Neural General Circulation Models.
CoRR, 2023

WeatherBench 2: A benchmark for the next generation of data-driven global weather models.
CoRR, 2023

2022
GraphCast: Learning skillful medium-range global weather forecasting.
CoRR, 2022

Efficient and Modular Implicit Differentiation.
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.
CoRR, 2021

Variational Data Assimilation with a Learned Inverse Observation Operator.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Array programming with NumPy.
Nat., 2020

Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics.
CoRR, 2020

Lagrangian Neural Networks.
CoRR, 2020

2019
Inundation Modeling in Data Scarce Regions.
CoRR, 2019

Neural reparameterization improves structural optimization.
CoRR, 2019

2018
Data-driven metasurface discovery.
CoRR, 2018

Assessing microscope image focus quality with deep learning.
BMC Bioinform., 2018

2017
The Cramer Distance as a Solution to Biased Wasserstein Gradients.
CoRR, 2017


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