Learning black- and gray-box chemotactic PDEs/closures from agent based Monte Carlo simulation data. - Seungjoon Lee; Yorgos M. Psarellis; Constantinos I. Siettos; Ioannis G. Kevrekidis (CoRR, 2022)

Limits of Entrainment of Circadian Neuronal Networks. - Yorgos M. Psarellis; Michail E. Kavousanakis; Michael A. Henson; Ioannis G. Kevrekidis (CoRR, 2022)

Physics-agnostic and Physics-infused machine learning for thin films flows: modeling, and predictions from small data. - Cristina P. Martin-Linares; Yorgos M. Psarellis; Georgios Karapetsas; Eleni D. Koronaki; Ioannis G. Kevrekidis (CoRR, 2023)

Equation-Free Computations as DDDAS Protocols for Bifurcation Studies: A Granular Chain Example. - Matthew O. Williams; Yorgos M. Psarellis; D. Pozharskiy; C. Chong; F. Li; J. Yang; Panayotis G. Kevrekidis; Ioannis G. Kevrekidis (CoRR, 2023)

From partial data to out-of-sample parameter and observation estimation with diffusion maps and geometric harmonics. - Eleni D. Koronaki; Nikolaos Evangelou; Yorgos M. Psarellis; Andreas G. Boudouvis; Ioannis G. Kevrekidis (Comput. Chem. Eng., 2023)

Active search for Bifurcations. - Yorgos M. Psarellis; Themistoklis P. Sapsis; Ioannis G. Kevrekidis (CoRR, 2024)

Data-driven discovery of chemotactic migration of bacteria via coordinate-invariant machine learning. - Yorgos M. Psarellis; Seungjoon Lee; Tapomoy Bhattacharjee; Sujit S. Datta; Juan M. Bello-Rivas; Ioannis G. Kevrekidis (BMC Bioinform., 2024)