2 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
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…