Data-driven control of agent-based models: An Equation/Variable-free machine learning approach. - Dimitrios G. Patsatzis; Lucia Russo; Ioannis G. Kevrekidis; Constantinos I. Siettos (J. Comput. Phys., 2023)

A physics-informed neural network method for the approximation of slow invariant manifolds for the general class of stiff systems of ODEs. - Dimitrios G. Patsatzis; Lucia Russo; Constantinos I. Siettos (CoRR, 2024)

Learning the Latent dynamics of Fluid flows from High-Fidelity Numerical Simulations using Parsimonious Diffusion Maps. - Alessandro Della Pia; Dimitrios G. Patsatzis; Lucia Russo; Constantinos I. Siettos (CoRR, 2024)

Slow Invariant Manifolds of Fast-Slow Systems of ODEs with Physics-Informed Neural Networks. - Dimitrios G. Patsatzis; Lucia Russo; Constantinos I. Siettos (SIAM J. Appl. Dyn. Syst., 2024)

Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning. - Dimitrios G. Patsatzis; Gianluca Fabiani; Lucia Russo; Constantinos I. Siettos (SIAM J. Sci. Comput., 2024)

GoRINNs: Godunov-Riemann informed neural networks for learning hyperbolic conservation laws. - Dimitrios G. Patsatzis; Mario di Bernardo; Lucia Russo; Constantinos I. Siettos (J. Comput. Phys., 2025)

A Hybrid Neural Network - Polynomial Series Scheme for Learning Invariant Manifolds of Discrete Dynamical Systems. - Dimitrios G. Patsatzis; Nikolaos Kazantzis; Ioannis G. Kevrekidis; Constantinos I. Siettos (CoRR, 2025)

Surrogate normal-forms for the numerical bifurcation and stability analysis of navier-stokes flows via machine learning. - Alessandro Della Pia; Dimitrios G. Patsatzis; Gianluigi Rozza; Lucia Russo; Constantinos I. Siettos (CoRR, 2025)

Next Generation Equation-Free Multiscale Modelling of Crowd Dynamics via Machine Learning. - Hector Vargas Alvarez; Dimitrios G. Patsatzis; Lucia Russo; Ioannis G. Kevrekidis; Constantinos I. Siettos (CoRR, 2025)