Prosjekter
Kontaktperson, prosjekter
Ekspertise
Kontaktperson, ekspertise
Publikasjoner
- Pseudo-Hamiltonian neural networks for learning partial differential equations
- A Reinforcement Learning framework for Wake Steering of Wind Turbines
- Constraint Preserving Mixers for the Quantum Approximate Optimization Algorithm Les publikasjonen
- Efficient numerical simulation of vacuum swing adsorption using automatic differentiation
- Convergence Rates of Monotone Schemes for Conservation Laws for Data with Unbounded Total Variation Les publikasjonen
- Iterative Surrogate Model Optimization (ISMO): An active learning algorithm for PDE constrained optimization with deep neural networks Les publikasjonen
- A multi-level procedure for enhancing accuracy of machine learning algorithms
- Density-consistent Initialization of SPH on a Regular Cartesian Grid: Comparative Numerical Study of 10 Smoothing Kernels in 1, 2 and 3 Dimensions
- A Framework for OpenGL Client-Server Rendering Les publikasjonen
Annen formidling
- Efficient in-situ machine learning workflows for simulation of subsurface CO2 storage in OPM Flow
- Value of information to design cost effective monitoring schemes: a Sleipner case study
- Rank Histogram Estimators for Multi-Level Data Assimilation
- A new simulation framework for modelling CO2 adsorption processes
- Pseudo-Hamiltonian neural networks
- Pseudo-Hamiltonian neural networks for learning PDEs
- Multi-level Data Assimilation: Statistical Background and Application to the Shallow-Water Model
- Efficient numerical simulation of vacuum swing adsorption using automatic differentiation
- Hva er algoritmer? Og styrer de livene våre?
- Geilo Winter School in eScience on Learning from Data