default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDPhaedon-Stelios Koutsourelakis
Person information
- affiliation: Technical University of Munich, Germany
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[j15]Atul Agrawal
, Phaedon-Stelios Koutsourelakis:
A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty. J. Comput. Phys. 508: 112982 (2024)- [i17]Matthaios Chatzopoulos, Phaedon-Stelios Koutsourelakis:
Physics-Aware Neural Implicit Solvers for multiscale, parametric PDEs with applications in heterogeneous media. CoRR abs/2405.19019 (2024) - [i16]Vincent C. Scholz, Yaohua Zang, Phaedon-Stelios Koutsourelakis:
Weak neural variational inference for solving Bayesian inverse problems without forward models: applications in elastography. CoRR abs/2407.20697 (2024) - 2023
- [i15]Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis, Petros Koumoutsakos:
Interpretable reduced-order modeling with time-scale separation. CoRR abs/2303.02189 (2023) - [i14]Atul Agrawal, Phaedon-Stelios Koutsourelakis:
A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty. CoRR abs/2307.02432 (2023) - [i13]Atul Agrawal, Kislaya Ravi, Phaedon-Stelios Koutsourelakis, Hans-Joachim Bungartz:
Multi-fidelity Constrained Optimization for Stochastic Black Box Simulators. CoRR abs/2311.15137 (2023) - [i12]Daniel Andrés Arcones, Martin Weiser, Phaedon-Stelios Koutsourelakis, Jörg F. Unger:
Model bias identification for Bayesian calibration of stochastic digital twins of bridges. CoRR abs/2312.00664 (2023) - 2022
- [i11]Sebastian Kaltenbach, Paris Perdikaris, Phaedon-Stelios Koutsourelakis:
Semi-supervised Invertible DeepONets for Bayesian Inverse Problems. CoRR abs/2209.02772 (2022) - 2021
- [j14]Maximilian Rixner, Phaedon-Stelios Koutsourelakis:
A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observables. J. Comput. Phys. 434: 110218 (2021) - [c2]Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis:
Physics-aware, probabilistic model order reduction with guaranteed stability. ICLR 2021 - [i10]Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis:
Physics-aware, probabilistic model order reduction with guaranteed stability. CoRR abs/2101.05834 (2021) - [i9]Maximilian Rixner, Phaedon-Stelios Koutsourelakis:
Self-supervised optimization of random material microstructures in the small-data regime. CoRR abs/2108.02606 (2021) - [i8]Jonas Eichelsdörfer, Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis:
Physics-enhanced Neural Networks in the Small Data Regime. CoRR abs/2111.10329 (2021) - 2020
- [j13]Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis:
Incorporating physical constraints in a deep probabilistic machine learning framework for coarse-graining dynamical systems. J. Comput. Phys. 419: 109673 (2020) - [i7]Jonas Nitzler, Jonas Biehler, Niklas Fehn, Phaedon-Stelios Koutsourelakis, Wolfgang A. Wall:
A Generalized Probabilistic Learning Approach for Multi-Fidelity Uncertainty Propagation in Complex Physical Simulations. CoRR abs/2001.02892 (2020) - [i6]Markus Schöberl, Nicholas Zabaras, Phaedon-Stelios Koutsourelakis:
Embedded-physics machine learning for coarse-graining and collective variable discovery without data. CoRR abs/2002.10148 (2020) - [i5]Maximilian Rixner, Phaedon-Stelios Koutsourelakis:
A probabilistic generative model for semi-supervised training of coarse-grained surrogates and enforcing physical constraints through virtual observables. CoRR abs/2006.01789 (2020)
2010 – 2019
- 2019
- [j12]Yinhao Zhu, Nicholas Zabaras, Phaedon-Stelios Koutsourelakis, Paris Perdikaris:
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data. J. Comput. Phys. 394: 56-81 (2019) - [j11]Constantin Grigo, Phaedon-Stelios Koutsourelakis:
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime. J. Comput. Phys. 397 (2019) - [j10]Constantin Grigo, Phaedon-Stelios Koutsourelakis:
Bayesian Model and Dimension Reduction for Uncertainty Propagation: Applications in Random Media. SIAM/ASA J. Uncertain. Quantification 7(1): 292-323 (2019) - [i4]Yinhao Zhu, Nicholas Zabaras, Phaedon-Stelios Koutsourelakis, Paris Perdikaris:
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data. CoRR abs/1901.06314 (2019) - [i3]Constantin Grigo, Phaedon-Stelios Koutsourelakis:
A physics-aware, probabilistic machine learning framework for coarse-graining high-dimensional systems in the Small Data regime. CoRR abs/1902.03968 (2019) - 2018
- [i2]Constantin Grigo, Phaedon-Stelios Koutsourelakis:
A data-driven model order reduction approach for Stokes flow through random porous media. CoRR abs/1806.08117 (2018) - [i1]Markus Schöberl, Nicholas Zabaras, Phaedon-Stelios Koutsourelakis:
Predictive Collective Variable Discovery with Deep Bayesian Models. CoRR abs/1809.06913 (2018) - 2017
- [j9]Franck Monmont, Phaedon-Stelios Koutsourelakis:
Multimodal, high-dimensional, model-based, Bayesian inverse problems with applications in biomechanics. J. Comput. Phys. 329: 91-125 (2017) - [j8]Markus Schöberl, Nicholas Zabaras, Phaedon-Stelios Koutsourelakis:
Predictive coarse-graining. J. Comput. Phys. 333: 49-77 (2017) - 2016
- [j7]Phaedon-Stelios Koutsourelakis:
Variational Bayesian strategies for high-dimensional, stochastic design problems. J. Comput. Phys. 308: 124-152 (2016) - [j6]Phaedon-Stelios Koutsourelakis, Nicholas Zabaras, Michele Girolami:
Special Issue: Big data and predictive computational modeling. J. Comput. Phys. 321: 1252-1254 (2016) - 2012
- [j5]Ilias Bilionis, Phaedon-Stelios Koutsourelakis:
Free energy computations by minimization of Kullback-Leibler divergence: An efficient adaptive biasing potential method for sparse representations. J. Comput. Phys. 231(9): 3849-3870 (2012) - 2011
- [j4]Phaedon-Stelios Koutsourelakis, Elias Bilionis:
Scalable Bayesian Reduced-Order Models for Simulating High-Dimensional Multiscale Dynamical Systems. Multiscale Model. Simul. 9(1): 449-485 (2011)
2000 – 2009
- 2009
- [j3]Phaedon-Stelios Koutsourelakis:
A multi-resolution, non-parametric, Bayesian framework for identification of spatially-varying model parameters. J. Comput. Phys. 228(17): 6184-6211 (2009) - [j2]Phaedon-Stelios Koutsourelakis:
Accurate Uncertainty Quantification Using Inaccurate Computational Models. SIAM J. Sci. Comput. 31(5): 3274-3300 (2009) - 2008
- [c1]Phaedon-Stelios Koutsourelakis, Tina Eliassi-Rad:
Finding Mixed-Memberships in Social Networks. AAAI Spring Symposium: Social Information Processing 2008: 48-53 - 2007
- [j1]Phaedon-Stelios Koutsourelakis:
Stochastic upscaling in solid mechanics: An excercise in machine learning. J. Comput. Phys. 226(1): 301-325 (2007)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-25 20:08 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
