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Pantelis R. Vlachas
Pantelis R. Vlachas
ETH Zurich, Harvard SEAS, AI2C Technologies
Verified email at ethz.ch
Title
Cited by
Cited by
Year
Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks
PR Vlachas, W Byeon, ZY Wan, TP Sapsis, P Koumoutsakos
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2018
4852018
Backpropagation algorithms and reservoir computing in recurrent neural networks for the forecasting of complex spatiotemporal dynamics
PR Vlachas, J Pathak, BR Hunt, TP Sapsis, M Girvan, E Ott, ...
Neural Networks 126, 191-217, 2020
3362020
Data-assisted reduced-order modeling of extreme events in complex dynamical systems
ZY Wan, P Vlachas, P Koumoutsakos, T Sapsis
PloS one 13 (5), e0197704, 2018
2322018
Multiscale simulations of complex systems by learning their effective dynamics
PR Vlachas, G Arampatzis, C Uhler, P Koumoutsakos
Nature Machine Intelligence 4 (4), 359-366, 2022
882022
Forecasting of spatio-temporal chaotic dynamics with recurrent neural networks: A comparative study of reservoir computing and backpropagation algorithms
PR Vlachas, J Pathak, BR Hunt, TP Sapsis, M Girvan, E Ott, ...
arXiv preprint arXiv:1910.05266, 2019
332019
Accelerated simulations of molecular systems through learning of effective dynamics
PR Vlachas, J Zavadlav, M Praprotnik, P Koumoutsakos
Journal of Chemical Theory and Computation 18 (1), 538-549, 2021
322021
Learning the effective dynamics of complex multiscale systems
PR Vlachas, G Arampatzis, C Uhler, P Koumoutsakos
arXiv preprint arXiv:2006.13431, 2020
92020
Adaptive learning of effective dynamics: Adaptive real-time, online modeling for complex systems
I Kičić, PR Vlachas, G Arampatzis, M Chatzimanolakis, L Guibas, ...
arXiv preprint arXiv:2304.01732, 2023
42023
Learning from predictions: Fusing training and autoregressive inference for long-term spatiotemporal forecasts
PR Vlachas, P Koumoutsakos
arXiv preprint arXiv:2302.11101, 2023
42023
Adaptive learning of effective dynamics for online modeling of complex systems
I Kičić, PR Vlachas, G Arampatzis, M Chatzimanolakis, L Guibas, ...
Computer Methods in Applied Mechanics and Engineering 415, 116204, 2023
32023
Learning and forecasting the effective dynamics of complex systems across scales
PR Vlachas
ETH Zurich, 2022
32022
A fast analytical approach for static power-down mode analysis
M Zwerger, PR Vlachas, H Graeb
2015 IEEE International Conference on Electronics, Circuits, and Systems …, 2015
22015
Improved Memories Learning
F Varoli, G Novati, PR Vlachas, P Koumoutsakos
arXiv preprint arXiv:2008.10433, 2020
12020
RefreshNet: Learning Multiscale Dynamics through Hierarchical Refreshing
J Farooq, D Rafiq, PR Vlachas, MA Bazaz
arXiv preprint arXiv:2401.13282, 2024
2024
Alanine dipeptide data
PR Vlachas
ETH Zurich, Computational Science & Engineering Laboratory, 2021
2021
Distributional Reinforcement Learning
PR Vlachas
2019
2 Publications and presentations
P Vlachas, W Byeon, ZY Wan, T Sapsis, P Koumoutsakos
dynamical systems 3, e1701533, 2017
2017
A Comparison of ADMM and AMA for MPC
P Vlachas
Automatic Control lab (IfA), ETH Zurich, 2016
2016
Session A1L-A: Analog Circuit Techniques I
ASP Parallel
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Articles 1–19