Sparse Physics-based Gaussian Process for Multi-output Regression using Variational Inference. - Ankit Chiplunkar; Emmanuel Rachelson; Michele Colombo; Joseph Morlier (ICPRAM, 2016)

Approximate Inference in Related Multi-output Gaussian Process Regression. - Ankit Chiplunkar; Emmanuel Rachelson; Michele Colombo; Joseph Morlier (ICPRAM (Revised Selected Papers), 2016)

ELM Preference Learning for Physiological Data. - Davide Bacciu; Michele Colombo; Davide Morelli; David Plans (ESANN, 2017)

Randomized neural networks for preference learning with physiological data. - Davide Bacciu; Michele Colombo; Davide Morelli; David Plans (Neurocomputing, 2018)

Development of digitally obtainable 10-year risk scores for depression and anxiety in the general population. - Davide Morelli; N. Dolezalova; S. Ponzo; Michele Colombo; David Plans (CoRR, 2021)

PC-GAU: PCA Basis of Scattered Gaussians for Shape Matching via Functional Maps. - Michele Colombo; Giacomo Boracchi; Simone Melzi (STAG, 2022)

Experimental Investigation of 5G Base Station Functionalities in Reverberation Chamber at Millimeter-Wave. - Michele Colombo; Riccardo Diamanti; Luca Bastianelli; Gabriele Gradoni; Emanuel Colella; Valter Mariani Primiani; Franco Moglie; Davide Micheli (IEEE Access, 2023)

Extracting a functional representation from a dictionary for non-rigid shape matching. - Michele Colombo; Giacomo Boracchi; Simone Melzi (Comput. Graph., 2023)

Investigation of Water and Mud Effects on the Propagation of Real 5G Signal by Using the Reverberation Chamber. - Luca Bastianelli; Riccardo Diamanti; Alfredo De Leo; Emanuel Colella; Michele Colombo; Valter Mariani Primiani; Franco Moglie; Davide Micheli (IEEE Access, 2025)