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09/14/2023
Improving physics-informed DeepONets with hard constraints
Current physics-informed (standard or operator) neural networks still re...
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04/20/2023
Towards replacing precipitation ensemble predictions systems using machine learning
Precipitation forecasts are less accurate compared to other meteorologic...
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04/18/2023
M-ENIAC: A machine learning recreation of the first successful numerical weather forecasts
In 1950 the first successful numerical weather forecast was obtained by ...
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03/13/2023
Improving physics-informed neural networks with meta-learned optimization
We show that the error achievable using physics-informed neural networks...
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01/12/2023
Model-free machine learning of conservation laws from data
We present a machine learning based method for learning first integrals ...
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06/07/2022
Improving trajectory calculations using deep learning inspired single image superresolution
Lagrangian trajectory or particle dispersion models as well as semi-Lagr...
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05/18/2022
Computing the ensemble spread from deterministic weather predictions using conditional generative adversarial networks
Ensemble prediction systems are an invaluable tool for weather forecasti...
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07/06/2021
Invariant Variational Schemes for Ordinary Differential Equations
We propose a novel algorithmic method for constructing invariant variati...
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04/01/2021
Physics-informed neural networks for the shallow-water equations on the sphere
We propose the use of physics-informed neural networks for solving the s...
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07/01/2019
