Graphene epsilon-near-zero plasmonic crystals. - Marios Mattheakis; Matthias Maier; Wei Xi Boo; Efthimios Kaxiras (NANOCOM, 2019)

Physical Symmetries Embedded in Neural Networks. - Marios Mattheakis; Pavlos Protopapas; David Sondak; Marco Di Giovanni 001; Efthimios Kaxiras (CoRR, 2019)

Sensorless Node Architecture for Events detection in Self-Powered Nanosensor Networks. - Najm Hassan; Marios Mattheakis; Ming Ding 001 (Nano Commun. Networks, 2019)

Hamiltonian Neural Networks for solving differential equations. - Marios Mattheakis; David Sondak; Akshunna S. Dogra; Pavlos Protopapas (CoRR, 2020)

Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread. - Alessandro Paticchio; Tommaso Scarlatti; Marios Mattheakis; Pavlos Protopapas; Marco Brambilla 001 (CoRR, 2020)

Unsupervised Neural Networks for Quantum Eigenvalue Problems. - Henry Jin; Marios Mattheakis; Pavlos Protopapas (CoRR, 2020)

LAN: A Materials Notation for Two-Dimensional Layered Assemblies. - Georgios A. Tritsaris; Yiqi Xie; Alexander M. Rush; Stephen Carr; Marios Mattheakis; Efthimios Kaxiras (J. Chem. Inf. Model., 2020)

NeuroDiffEq: A Python package for solving differential equations with neural networks. - Feiyu Chen; David Sondak; Pavlos Protopapas; Marios Mattheakis; Shuheng Liu 001; Devansh Agarwal; Marco Di Giovanni 001 (J. Open Source Softw., 2020)

A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function. - Tiago A. E. Ferreira; Marios Mattheakis; Pavlos Protopapas (CoRR, 2021)

Encoding Involutory Invariance in Neural Networks. - Anwesh Bhattacharya; Marios Mattheakis; Pavlos Protopapas (CoRR, 2021)

Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems. - Shaan Desai; Marios Mattheakis; David Sondak; Pavlos Protopapas; Stephen J. Roberts (CoRR, 2021)

Unsupervised Reservoir Computing for Solving Ordinary Differential Equations. - Marios Mattheakis; Hayden Joy; Pavlos Protopapas (CoRR, 2021)

Modeling the effect of the vaccination campaign on the Covid-19 pandemic. - Mattia Angeli; Georgios Neofotistos; Marios Mattheakis; Efthimios Kaxiras (CoRR, 2021)

One-Shot Transfer Learning of Physics-Informed Neural Networks. - Shaan Desai; Marios Mattheakis; Hayden Joy; Pavlos Protopapas; Stephen J. Roberts (CoRR, 2021)

Encoding Involutory Invariances in Neural Networks. - Anwesh Bhattacharya; Marios Mattheakis; Pavlos Protopapas (IJCNN, 2022)

Physics-Informed Neural Networks for Quantum Eigenvalue Problems. - Henry Jin; Marios Mattheakis; Pavlos Protopapas (IJCNN, 2022)

RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization. - Hayden Joy; Marios Mattheakis; Pavlos Protopapas (CoRR, 2022)

Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows. - Raphaël Pellegrin; Blake Bullwinkel; Marios Mattheakis; Pavlos Protopapas (CoRR, 2022)

First principles physics-informed neural network for quantum wavefunctions and eigenvalue surfaces. - Marios Mattheakis; Gabriel R. Schleder; Daniel T. Larson; Efthimios Kaxiras (CoRR, 2022)

Reservoir Computing for Solving Ordinary Differential Equations. - Marios Mattheakis; Hayden Joy; Pavlos Protopapas (Int. J. Artif. Intell. Tools, 2023)