Search Results - "Koutsourelakis, Phaedon-Stelios" :: K.UTB vyhledávací portál

Predictive collective variable discovery with deep Bayesian models

by Schöberl, Markus, Zabaras, Nicholas, Koutsourelakis, Phaedon-Stelios
Published in The Journal of chemical physics (14.01.2019)

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Application of Machine Learning Algorithms to Metadynamics for the Elucidation of the Binding Modes and Free Energy Landscape of Drug/Target Interactions: a Case Study

by Siddiqui, Gohar Ali, Stebani, Julia A., Wragg, Darren, Koutsourelakis, Phaedon‐Stelios, Casini, Angela, Gagliardi, Alessio
Published in Chemistry : a European journal (08.11.2023)

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A novel Bayesian strategy for the identification of spatially varying material properties and model validation: an application to static elastography

by Koutsourelakis, Phaedon-Stelios
Published in International journal for numerical methods in engineering (20.07.2012)

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Self-supervised optimization of random material microstructures in the small-data regime

by Rixner, Maximilian, Koutsourelakis, Phaedon-Stelios
Published in npj computational materials (21.03.2022)

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Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

by Zhu, Yinhao, Zabaras, Nicholas, Koutsourelakis, Phaedon-Stelios, Perdikaris, Paris
Published in Journal of computational physics (01.10.2019)

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Multifidelity approaches for uncertainty quantification

by Biehler, Jonas, Mäck, Markus, Nitzler, Jonas, Hanss, Michael, Koutsourelakis, Phaedon‐Stelios, Wall, Wolfgang A.
Published in Mitteilungen der Gesellschaft für Angewandte Mathematik und Mechanik (01.05.2019)

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A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty

by Agrawal, Atul, Koutsourelakis, Phaedon-Stelios
Published in Journal of computational physics (01.07.2024)

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Incorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systems

by Kaltenbach, Sebastian, Koutsourelakis, Phaedon-Stelios
Published in Journal of computational physics (15.10.2020)

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A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime

by Grigo, Constantin, Koutsourelakis, Phaedon-Stelios
Published in Journal of computational physics (15.11.2019)

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Semi-supervised invertible neural operators for Bayesian inverse problems

by Kaltenbach, Sebastian, Perdikaris, Paris, Koutsourelakis, Phaedon-Stelios
Published in Computational mechanics (01.09.2023)

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A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observables

by Rixner, Maximilian, Koutsourelakis, Phaedon-Stelios
Published in Journal of computational physics (01.06.2021)

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Predictive coarse-graining

by Schöberl, Markus, Zabaras, Nicholas, Koutsourelakis, Phaedon-Stelios
Published in Journal of computational physics (15.03.2017)

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A generalized probabilistic learning approach for multi-fidelity uncertainty quantification in complex physical simulations

by Nitzler, Jonas, Biehler, Jonas, Fehn, Niklas, Koutsourelakis, Phaedon-Stelios, Wall, Wolfgang A.
Published in Computer methods in applied mechanics and engineering (01.10.2022)

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Accurate Uncertainty Quantification Using Inaccurate Computational Models

by Koutsourelakis, Phaedon-Stelios
Published in SIAM journal on scientific computing (01.01.2009)

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From concrete mixture to structural design—a holistic optimization procedure in the presence of uncertainties

by Agrawal, Atul, Tamsen, Erik, Unger, Jörg F., Koutsourelakis, Phaedon-Stelios
Published in Data-Centric Engineering (Online) (01.01.2024)

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Model-based structural health monitoring of naval ship hulls

by Stull, Christopher J., Earls, Christopher J., Koutsourelakis, Phaedon-Stelios
Published in Computer methods in applied mechanics and engineering (01.02.2011)

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