3 papers
stat.ML2026
Deep Adaptive Model-Based Design of Experiments
Arno Strouwen, Sebastian Micluţa-Câmpeanu
Model-based design of experiments (MBDOE) is essential for efficient parameter estimation in nonlinear dynamical systems. However, conventional adaptive MBDOE requires costly poste…
stat.ML2026
Experimental Design for Missing Physics
Arno Strouwen, Sebastián Micluţa-Câmpeanu
For most process systems, knowledge of the model structure is incomplete. This missing physics must then be learned from experimental data. Recently, a combination of universal dif…
cs.CE2026
Scientific Machine Learning-assisted Model Discovery from Telemetry Data
Sebastian Micluta-Campeanu, Avinash Subramanian, Anas Abdelrehim +4
Calibration of dynamic models to data is an important step in building building digital twins of HVAC equipment, thermal loads and control systems. Sometimes, when a model fails to…