3 papers
cs.LG2026
Scalable Physics-Informed Neural Differential Equations and Data-Driven Algorithms for HVAC Systems
Hanfeng Zhai, Hongtao Qiao, Hassan Mansour +1
We present a scalable, data-driven simulation framework for large-scale heating, ventilation, and air conditioning (HVAC) systems that couples physics-informed neural ordinary diff…
cs.LG2025
Probabilistic Forecasting for Building Energy Systems using Time-Series Foundation Models
Young Jin Park, Francois Germain, Jing Liu +6
Decision-making in building energy systems critically depends on the predictive accuracy of relevant time-series models. In scenarios lacking extensive data from a target building,…
cs.LG2025
Meta-Learning for Physically-Constrained Neural System Identification
Ankush Chakrabarty, Gordon Wichern, Vedang M. Deshpande +3
We present a gradient-based meta-learning framework for rapid adaptation of neural state-space models (NSSMs) for black-box system identification. When applicable, we also incorpor…