Data-driven cortical clustering to provide a family of plausible solutions to M/EEG inverse problem. - Kostiantyn Maksymenko; Maureen Clerc; Théodore Papadopoulo (CoRR, 2018)

Novel algorithmic approaches for the forward and inverse M/EEG problems. (Nouvelles approches algorithmiques pour les problèmes directs et inverses en M/EEG). - Kostiantyn Maksymenko (2019)

Fast Approximation of EEG Forward Problem and Application to Tissue Conductivity Estimation. - Kostiantyn Maksymenko; Maureen Clerc; Théodore Papadopoulo (IEEE Trans. Medical Imaging, 2020)

Human Biophysics as Network Weights: Conditional Generative Models for Ultra-fast Simulation. - Shihan Ma; Alexander Kenneth Clarke; Kostiantyn Maksymenko; Samuel Deslauriers-Gauthier; Xinjun Sheng; Xiangyang Zhu; Dario Farina (CoRR, 2022)

NeuroMotion: Open-source platform with neuromechanical and deep network modules to generate surface EMG signals during voluntary movement. - Shihan Ma; Irene Mendez Guerra; Arnault H. Caillet; Jiamin Zhao; Alexander Kenneth Clarke; Kostiantyn Maksymenko; Samuel Deslauriers-Gauthier; Xinjun Sheng; Xiangyang Zhu; Dario Farina (PLoS Comput. Biol., 2024)

Conditional Generative Models for Simulation of EMG During Naturalistic Movements. - Shihan Ma; Alexander Kenneth Clarke; Kostiantyn Maksymenko; Samuel Deslauriers-Gauthier; Xinjun Sheng; Xiangyang Zhu; Dario Farina (IEEE Trans. Neural Networks Learn. Syst., 2025)