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
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- University of California, BerkeleyUS2 papers
9 papers · 1 filter
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…
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…
Adaptive sampling strategies for risk-averse stochastic optimization with constraints
Florian Beiser, Brendan Keith, Simon Urbainczyk +1
We introduce adaptive sampling methods for stochastic programs with deterministic constraints. First, we propose and analyze a variant of the stochastic projected gradient method w…
Understanding coordination in global software engineering: A mixed-methods study on the use of meetings and Slack
Viktoria Stray, Nils Brede Moe
Given the relevance of coordination in the field of global software engineering, this work was carried out to further understand coordination mechanisms. Specifically, we investiga…
Multifidelity Computing for Coupling Full and Reduced Order Models
Shady E. Ahmed, Omer San, Kursat Kara +2
Hybrid physics-machine learning models are increasingly being used in simulations of transport processes. Many complex multiphysics systems relevant to scientific and engineering a…
Quantifying the Re-identification Risk of Event Logs for Process Mining
S. Nuñez von Voigt, S. A. Fahrenkrog-Petersen, D. Janssen +5
Event logs recorded during the execution of business processes constitute a valuable source of information. Applying process mining techniques to them, event logs may reveal the ac…