A fast analytical approach for static power-down mode analysis. - Michael Zwerger; Pantelis-Rafail Vlachas; Helmut Graeb (ICECS, 2015)

Data-Driven Forecasting of High-Dimensional Chaotic Systems with Long-Short Term Memory Networks. - Pantelis-Rafail Vlachas; Wonmin Byeon; Zhong Yi Wan; Themistoklis P. Sapsis; Petros Koumoutsakos (CoRR, 2018)

Forecasting of Spatio-temporal Chaotic Dynamics with Recurrent Neural Networks: a comparative study of Reservoir Computing and Backpropagation Algorithms. - Pantelis-Rafail Vlachas; Jaideep Pathak; Brian R. Hunt; Themistoklis P. Sapsis; Michelle Girvan; Edward Ott; Petros Koumoutsakos (CoRR, 2019)

Learning the Effective Dynamics of Complex Multiscale Systems. - Pantelis-Rafail Vlachas; Georgios Arampatzis; Caroline Uhler; Petros Koumoutsakos (CoRR, 2020)

Improved Memories Learning. - Francesco Varoli; Guido Novati; Pantelis-Rafail Vlachas; Petros Koumoutsakos (CoRR, 2020)

Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics. - Pantelis-Rafail Vlachas; Jaideep Pathak; Brian R. Hunt; Themistoklis P. Sapsis; Michelle Girvan; Edward Ott; Petros Koumoutsakos (Neural Networks, 2020)

Accelerated Simulations of Molecular Systems through Learning of their Effective Dynamics. - Pantelis-Rafail Vlachas; Julija Zavadlav; Matej Praprotnik; Petros Koumoutsakos (CoRR, 2021)

Multiscale simulations of complex systems by learning their effective dynamics. - Pantelis-Rafail Vlachas; Georgios Arampatzis; Caroline Uhler; Petros Koumoutsakos (Nat. Mach. Intell., 2022)

Learning and Forecasting the Effective Dynamics of Complex Systems Across Scales. - Pantelis-Rafail Vlachas (2022)

Learning from Predictions: Fusing Training and Autoregressive Inference for Long-Term Spatiotemporal Forecasts. - Pantelis-Rafail Vlachas; Petros Koumoutsakos (CoRR, 2023)

Adaptive learning of effective dynamics: Adaptive real-time, online modeling for complex systems. - Ivica Kicic; Pantelis-Rafail Vlachas; Georgios Arampatzis; Michail Chatzimanolakis; Leonidas J. Guibas; Petros Koumoutsakos (CoRR, 2023)

Deconstructing Recurrence, Attention, and Gating: Investigating the transferability of Transformers and Gated Recurrent Neural Networks in forecasting of dynamical systems. - Hunter Scott Heidenreich; Pantelis-Rafail Vlachas; Petros Koumoutsakos (CoRR, 2024)