14 citations · 28 across the 6 of their papers we have counts for
6 papers
HourGlass: A probabilistic data-driven temporal downscaler for global and regional weather forecasting
Magnus Sikora Ingstad, Mariana C. A. Clare, Olav Ersland +16
Many forecast applications require high frequency temporal resolution, yet most state-of-the-art data-driven weather forecasting systems operate at 6-hourly resolution. Although di…
High-Resolution Probabilistic Data-Driven Weather Modeling with a Stretched-Grid
Even Marius Nordhagen, Håvard Homleid Haugen, Magnus Sikora Ingstad +9
We present a probabilistic data-driven weather model providing ensembles of high spatial resolution realizations of 87 variables at arbitrary ensemble size and forecast length. The…
Regional data-driven weather modeling with a global stretched-grid
Thomas Nils Nipen, Håvard Homleid Haugen, Magnus Sikora Ingstad +11
A data-driven model (DDM) suitable for regional weather forecasting applications is presented. The model extends the Artificial Intelligence Forecasting System by introducing a str…
Tailoring Frictional Properties of Surfaces Using Diffusion Models
Even Marius Nordhagen, Henrik Andersen Sveinsson, Anders Malthe-Sørenssen
This Letter introduces an approach for precisely designing surface friction properties using a conditional generative machine learning model, specifically a diffusion denoising pro…
Diffusion-driven frictional aging in silicon carbide
Even Marius Nordhagen, Henrik Andersen Sveinsson, Anders Malthe-Sørenssen
Friction is the force resisting relative motion of objects. The force depends on material properties, loading conditions and external factors such as temperature and humidity, but…
Efficient Solutions of Fermionic Systems using Artificial Neural Networks
Even M. Nordhagen, Jane M. Kim, Bryce Fore +2
We discuss differences and similarities between variational Monte Carlo approaches that use conventional and artificial neural network parameterizations of the ground-state wave fu…