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Foundation Models for the Electric Power Grid
Hendrik Hamann
, Blazhe Gjorgiev
, Thomas Brunschwiler
, Leonardo Martins
, Alban Puech
, Anna Varbella
, Jonas Weiss
, Juan Bernabe-Moreno
, Alexandre Masse
,
Seong Choi
, Ian Foster
,
Bri-Mathias Hodge
, Rishabh Jain
, Kibaek Kim
, Vincent Mai
, Francois Miralles
, Martin De Montigny
, Octavio Ramos-Leanos
, Hussein Supreme
, Le Xie
El-Nasser Youssef, Arnaud Zinflou, Alexander Belyi, Ricardo Bessa, Bishnu Bhattarai, Johannes Schmude, Stanislav Sobolevsky
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Power Systems Engineering
Grid Planning and Analysis Center
IBM
ETH Zurich
Equilibrium Energy
Ecole Polytechnique Federale de Lausanne
Hydro-Quebec
Argonne National Laboratory
The University of Chicago
University of Colorado Boulder
Harvard University
University of Porto
United States Department of Energy
Masaryk University
New York University
Research output
:
Contribution to journal
›
Article
›
peer-review
14
Scopus Citations
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Engineering
Power Grid
100%
Power Flow
50%
Energy Transition
50%
Climate Change
50%
Climatic Change
50%
Artificial Intelligence
50%
Deep Learning Method
50%
Computer Science
Electric Grids
100%
Use Case
50%
Graph Neural Network
50%
data grid
50%
Artificial Intelligence
50%
Deep Learning Method
50%
Climatic Change
50%
Mathematics
Power Grid
100%
Dominates
50%
Neural Network
50%
Deep Learning Method
50%
Earth and Planetary Sciences
Climate Change
100%
Artificial Intelligence
100%
Neuroscience
Neural Network
100%