Learning Physics between Digital Twins with Low-Fidelity Models and Physics-Informed Gaussian Processes. - Michail Spitieris; Ingelin Steinsland (CoRR, 2022)

Bayesian Calibration of Imperfect Computer Models using Physics-Informed Priors. - Michail Spitieris; Ingelin Steinsland (J. Mach. Learn. Res., 2023)

Enhancing Indoor Temperature Forecasting through Synthetic Data in Low-Data Regime. - Massimiliano Ruocco; Zachari Thiry; Alessandro Nocente; Michail Spitieris (SCAI, 2024)

Enhancing Indoor Temperature Forecasting through Synthetic Data in Low-Data Environments. - Zachari Thiry; Massimiliano Ruocco; Alessandro Nocente; Michail Spitieris (CoRR, 2024)

PIGPVAE: physics-informed gaussian process variational autoencoders. - Michail Spitieris; Massimiliano Ruocco; Abdulmajid Murad; Alessandro Nocente (Appl. Intell., 2025)