19 citations · 23 across the 3 of their papers we have counts for
3 papers
eess.SY2025
The curse of dimensionality: what lies beyond the capabilities of physics-informed neural networks
J. Penuela, H. Ouerdane
Physics-Informed Neural Networks (PINNs) have emerged as a promising framework for solving forward and inverse problems governed by differential equations. However, their reliabili…
eess.SY2025★ 4 cited
Indoor thermal comfort management: A Bayesian machine-learning approach to data denoising and dynamics prediction of HVAC systems
Javier Penuela, Sahar Moghimian Hoosh, Ilia Kamyshev +2
The optimal management of a building's microclimate to satisfy the occupants' needs and objectives in terms of comfort, energy efficiency, and costs is particularly challenging. Th…
physics.soc-ph2024★ 19 cited
The indoor agriculture industry: a promising player in demand response services
Javier Penuela, Cecile Ben, Stepan Boldyrev +2
Demand response (DR) programs currently cover about 2\% of the average annual global demand, which is far from contributing to the International Energy Agency's ``Net Zero by 2050'…