2 papers
stat.ML2025
PIGPVAE: Physics-Informed Gaussian Process Variational Autoencoders
Michail Spitieris, Massimiliano Ruocco, Abdulmajid Murad +1
Recent advances in generative AI offer promising solutions for synthetic data generation but often rely on large datasets for effective training. To address this limitation, we pro…
cs.LG2024
Enhancing Indoor Temperature Forecasting through Synthetic Data in Low-Data Environments
Zachari Thiry, Massimiliano Ruocco, Alessandro Nocente +1
Forecasting indoor temperatures is important to achieve efficient control of HVAC systems. In this task, the limited data availability presents a challenge as most of the available…