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
150 2022 Automated identification and deep classification of cut marks on bones and its paleoanthropological implications W Byeon, M Dominguez-Rodrigo, G Arampatzis, E Baquedano, ...
Journal of Computational Science 32, 36-43, 2019
53 2019 AI support for ethical decision-making around resuscitation: proceed with care N Biller-Andorno, A Ferrario, S Joebges, T Krones, F Massini, P Barth, ...
Journal of medical ethics 48 (3), 175-183, 2022
49 2022 Optimal sensor placement for artificial swimmers S Verma, C Papadimitriou, N Lüthen, G Arampatzis, P Koumoutsakos
Journal of Fluid Mechanics 884, A24, 2020
40 2020 Data driven inference for the repulsive exponent of the Lennard-Jones potential in molecular dynamics simulations L Kulakova, G Arampatzis, P Angelikopoulos, P Hadjidoukas, ...
Scientific reports 7 (1), 16576, 2017
35 2017 Data driven inference of the reproduction number (R 0 ) for COVID-19 before and after interventions for 51 European countries P Karnakov, G Arampatzis, I Kičić, F Wermelinger, D Wälchli, ...
MedRxiv, 2020.05. 21.20109314, 2020
34 2020 Hierarchical fractional-step approximations and parallel kinetic Monte Carlo algorithms G Arampatzis, MA Katsoulakis, P Plecháč, M Taufer, L Xu
Journal of Computational Physics 231 (23), 7795-7814, 2012
30 2012 Bayesian selection for coarse-grained models of liquid water J Zavadlav, G Arampatzis, P Koumoutsakos
Scientific reports 9 (1), 99, 2019
24 2019 Optimal flow sensing for schooling swimmers P Weber, G Arampatzis, G Novati, S Verma, C Papadimitriou, ...
Biomimetics 5 (1), 10, 2020
21 2020 Korali: Efficient and scalable software framework for Bayesian uncertainty quantification and stochastic optimization SM Martin, D Wälchli, G Arampatzis, AE Economides, P Karnakov, ...
Computer Methods in Applied Mechanics and Engineering 389, 114264, 2022
19 2022 Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations G Arampatzis, MA Katsoulakis
The Journal of chemical physics 140 (12), 2014
19 2014 Unravelling the viscoelastic, buffer-like mechanical behavior of tendons: A numerical quantitative study at the fibril-fiber scale N Karathanasopoulos, G Arampatzis, JF Ganghoffer
Journal of the mechanical behavior of biomedical materials 90, 256-263, 2019
18 2019 Accelerated sensitivity analysis in high-dimensional stochastic reaction networks G Arampatzis, MA Katsoulakis, Y Pantazis
PloS one 10 (7), e0130825, 2015
17 2015 Optimal allocation of limited test resources for the quantification of COVID-19 infections M Chatzimanolakis, P Weber, G Arampatzis, D Wälchli, I Kičić, ...
medRxiv, 2020.11. 09.20228320, 2020
16 2020 Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics G Arampatzis, MA Katsoulakis, L Rey-Bellet
The Journal of Chemical Physics 144 (10), 2016
16 2016 Parallelization, processor communication and error analysis in lattice kinetic Monte Carlo G Arampatzis, MA Katsoulakis, P Plechác
SIAM Journal on Numerical Analysis 52 (3), 1156-1182, 2014
15 2014 Bayesian calibration of force fields for molecular simulations F Cailliez, P Pernot, F Rizzi, R Jones, O Knio, G Arampatzis, ...
Uncertainty quantification in multiscale materials modeling, 169-227, 2020
14 2020 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
13 2023 Hierarchical Bayesian uncertainty quantification for a model of the red blood cell A Economides, G Arampatzis, D Alexeev, S Litvinov, L Amoudruz, ...
Physical Review Applied 15 (3), 034062, 2021
12 2021 S -Leaping: An Adaptive, Accelerated Stochastic Simulation Algorithm, Bridging R -LeapingJ Lipková, G Arampatzis, P Chatelain, B Menze, P Koumoutsakos
Bulletin of mathematical biology 81 (8), 3074-3096, 2019
12 2019 
Petros KoumoutsakosHarvard UniversityПотвърден имейл адрес: seas.harvard.edu
