117 citations · 534 across the 30 of their papers we have counts for
5 papers · 1 filter
Unsupervised Neural Networks for Quantum Eigenvalue Problems
Henry Jin, Marios Mattheakis, Pavlos Protopapas
Eigenvalue problems are critical to several fields of science and engineering. We present a novel unsupervised neural network for discovering eigenfunctions and eigenvalues for dif…
Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread
Alessandro Paticchio, Tommaso Scarlatti, Marios Mattheakis +2
Studying the dynamics of COVID-19 is of paramount importance to understanding the efficiency of restrictive measures and develop strategies to defend against upcoming contagion wav…
Variational Integrator Graph Networks for Learning Energy Conserving Dynamical Systems
Shaan Desai, Marios Mattheakis, Stephen Roberts
Recent advances show that neural networks embedded with physics-informed priors significantly outperform vanilla neural networks in learning and predicting the long term dynamics o…
Electronic structure calculations of twisted multi-layer graphene superlattices
Georgios A. Tritsaris, Stephen Carr, Ziyan Zhu +6
Quantum confinement endows two-dimensional (2D) layered materials with exceptional physics and novel properties compared to their bulk counterparts. Although certain two- and few-l…
Hamiltonian neural networks for solving equations of motion
Marios Mattheakis, David Sondak, Akshunna S. Dogra +1
There has been a wave of interest in applying machine learning to study dynamical systems. We present a Hamiltonian neural network that solves the differential equations that gover…