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Panagiotis Angelikopoulos
Panagiotis Angelikopoulos
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Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
Bayesian uncertainty quantification and propagation in molecular dynamics simulations: a high performance computing framework
P Angelikopoulos, C Papadimitriou, P Koumoutsakos
The Journal of chemical physics 137 (14), 2012
2252012
On the Kapitza Resistance between Few-Layer Graphene and Water: Liquid Layering Effects
D Alexeev, J Chen, JH Walther, KP Giapis, P Angelikopoulos, ...
Nano Letters 15 (9), 5744–5749, 2015
1982015
Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models
PE Hadjidoukas, P Angelikopoulos, C Papadimitriou, P Koumoutsakos
Journal of Computational Physics 284, 1-21, 2015
1372015
Personalized radiotherapy design for glioblastoma: integrating mathematical tumor models, multimodal scans, and Bayesian inference
J Lipková, P Angelikopoulos, S Wu, E Alberts, B Wiestler, C Diehl, ...
IEEE transactions on medical imaging 38 (8), 1875-1884, 2019
1292019
X-TMCMC: Adaptive kriging for Bayesian inverse modeling
P Angelikopoulos, C Papadimitriou, P Koumoutsakos
Computer Methods in Applied Mechanics and Engineering 289, 409-428, 2015
1202015
Dispersing individual single-wall carbon nanotubes in aqueous surfactant solutions below the cmc
P Angelikopoulos, A Gromov, A Leen, O Nerushev, H Bock, ...
The Journal of Physical Chemistry C 114 (1), 2-9, 2010
952010
Homogeneous hydrophobic–hydrophilic surface patterns enhance permeation of nanoparticles through lipid membranes
P Gkeka, L Sarkisov, P Angelikopoulos
The journal of physical chemistry letters 4 (11), 1907-1912, 2013
882013
The science of dispersing carbon nanotubes with surfactants
P Angelikopoulos, H Bock
Physical chemistry chemical physics 14 (27), 9546-9557, 2012
802012
Membrane partitioning of anionic, ligand-coated nanoparticles is accompanied by ligand snorkeling, local disordering, and cholesterol depletion
P Gkeka, P Angelikopoulos, L Sarkisov, Z Cournia
PLoS computational biology 10 (12), e1003917, 2014
732014
Directed self-assembly of surfactants in carbon nanotube materials
P Angelikopoulos, H Bock
The Journal of Physical Chemistry B 112 (44), 13793-13801, 2008
722008
Dual nanoscale roughness on plasma-etched Si surfaces: Role of etch inhibitors
G Kokkoris, V Constantoudis, P Angelikopoulos, G Boulousis, ...
Physical Review B 76 (19), 193405, 2007
712007
Bayesian annealed sequential importance sampling: an unbiased version of transitional Markov chain Monte Carlo
S Wu, P Angelikopoulos, C Papadimitriou, P Koumoutsakos
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2018
622018
Self-assembly of anionic, ligand-coated nanoparticles in lipid membranes
P Angelikopoulos, L Sarkisov, Z Cournia, P Gkeka
Nanoscale 9 (3), 1040-1048, 2017
622017
Data driven, predictive molecular dynamics for nanoscale flow simulations under uncertainty
P Angelikopoulos, C Papadimitriou, P Koumoutsakos
The Journal of Physical Chemistry B 117 (47), 14808-14816, 2013
622013
A hierarchical Bayesian framework for force field selection in molecular dynamics simulations
S Wu, P Angelikopoulos, C Papadimitriou, R Moser, P Koumoutsakos
Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2016
552016
The differences in surfactant adsorption on carbon nanotubes and their bundles
P Angelikopoulos, H Bock
Langmuir 26 (2), 899-907, 2010
402010
Bayesian hierarchical models for uncertainty quantification in structural dynamics
GC Ballesteros, P Angelikopoulos, C Papadimitriou, P Koumoutsakos
Vulnerability, uncertainty, and risk: Quantification, mitigation, and …, 2014
392014
Bayesian uncertainty quantification and propagation for discrete element simulations of granular materials
PE Hadjidoukas, P Angelikopoulos, D Rossinelli, D Alexeev, ...
Computer Methods in Applied Mechanics and Engineering 282, 218-238, 2014
372014
Fusing heterogeneous data for the calibration of molecular dynamics force fields using hierarchical Bayesian models
S Wu, P Angelikopoulos, G Tauriello, C Papadimitriou, P Koumoutsakos
The Journal of chemical physics 145 (24), 2016
352016
Hierarchical stochastic model in Bayesian inference for engineering applications: Theoretical implications and efficient approximation
S Wu, P Angelikopoulos, JL Beck, P Koumoutsakos
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2019
322019
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