294 citations
- SINTEFNO50 papers
- Norwegian University of Science and TechnologyNO30 papers
- University of OsloNO8 papers
- Oklahoma State UniversityUS6 papers
- Centre for Arctic Gas Hydrate, Environment and ClimateNO2 papers
- NTNU SamfunnsforskningNO2 papers
- Oklahoma State University Oklahoma CityUS2 papers
- Simula Research LaboratoryNO2 papers
- Technische Universität BerlinDE2 papers
- UiT The Arctic University of NorwayNO2 papers
- University of BergenNO2 papers
- University of California, BerkeleyUS2 papers
Showing 2020 · cs.LGShow all
2 papers · 2 filters
cs.LG2020★ 135 cited
Physics guided machine learning using simplified theories
Suraj Pawar, Omer San, Burak Aksoylu +2
Recent applications of machine learning, in particular deep learning, motivate the need to address the generalizability of the statistical inference approaches in physical sciences…
cs.LG2020★ 19 cited
Deep Reinforcement Learning for Long Term Hydropower Production Scheduling
Signe Riemer-Sorensen, Gjert H. Rosenlund
We explore the use of deep reinforcement learning to provide strategies for long term scheduling of hydropower production. We consider a use-case where the aim is to optimise the y…