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Sensors (Basel, Switzerland)|July 16, 2020
Accounting for Modeling Errors and Inherent Structural Variability through a Hierarchical Bayesian Model Updating Approach: An OverviewMingming Song, Iman Behmanesh, Babak Moaveni, et al.
Sensors (Basel, Switzerland)|June 2, 2021
Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information TheoryTulay Ercan, Costas Papadimitriou
The Journal of Physical Chemistry. B|October 29, 2013
Data driven, predictive molecular dynamics for nanoscale flow simulations under uncertaintyPanagiotis Angelikopoulos, Costas Papadimitriou, Petros Koumoutsakos
The Journal of Chemical Physics|October 16, 2012
Bayesian uncertainty quantification and propagation in molecular dynamics simulations: a high performance computing frameworkPanagiotis Angelikopoulos, Costas Papadimitriou, Petros Koumoutsakos
Royal Society Open Science|December 12, 2019
Detection of arterial wall abnormalities via Bayesian model selectionKaren Larson, Clark Bowman, Costas Papadimitriou, et al.
The Journal of Chemical Physics|January 5, 2017
Fusing heterogeneous data for the calibration of molecular dynamics force fields using hierarchical Bayesian modelsStephen Wu, Panagiotis Angelikopoulos, Gerardo Tauriello, et al.
Scientific Reports|November 30, 2017
Data driven inference for the repulsive exponent of the Lennard-Jones potential in molecular dynamics simulationsLina Kulakova, Georgios Arampatzis, Panagiotis Angelikopoulos, et al.
Biomimetics (Basel, Switzerland)|March 19, 2020
Optimal Flow Sensing for Schooling SwimmersPascal Weber, Georgios Arampatzis, Guido Novati, et al.
Swiss Medical Weekly|July 18, 2020
Data-driven inference of the reproduction number for COVID-19 before and after interventions for 51 European countriesPetr Karnakov, Georgios Arampatzis, Ivica Kičić, et al.
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