52 citations · 216 across the 27 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2023★ 1 cited
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study
Robert Ferrando, Laurent Pagnier, Robert Mieth +4
This paper addresses the challenge of efficiently solving the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Awar…
cs.LG2018★ 11 cited
Principled Deep Neural Network Training through Linear Programming
Daniel Bienstock, Gonzalo Muñoz, Sebastian Pokutta
Deep learning has received much attention lately due to the impressive empirical performance achieved by training algorithms. Consequently, a need for a better theoretical understa…