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Katiana Kontolati
ORCID
Publication Activity (10 Years)
Years Active: 2021-2023
Publications (10 Years): 11
Top Topics
Manifold Learning
Partial Differential Equations
Unsupervised Learning
Predictive Accuracy
Top Venues
CoRR
J. Comput. Phys.
SoftwareX
Nat. Mac. Intell.
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Publications
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Dimitrios Tsapetis
,
Michael D. Shields
,
Dimitris G. Giovanis
,
Audrey Olivier
,
Lukás Novák
,
Promit Chakroborty
,
Himanshu Sharma
,
Mohit Chauhan
,
Katiana Kontolati
,
Lohit Vandanapu
,
Dimitrios Loukrezis
,
Michael Gardner
UQpy v4.1: Uncertainty Quantification with Python.
CoRR
(2023)
Katiana Kontolati
,
Somdatta Goswami
,
Michael D. Shields
,
George Em Karniadakis
On the influence of over-parameterization in manifold based surrogates and deep neural operators.
J. Comput. Phys.
479 (2023)
Katiana Kontolati
,
Somdatta Goswami
,
George Em Karniadakis
,
Michael D. Shields
Learning in latent spaces improves the predictive accuracy of deep neural operators.
CoRR
(2023)
Dimitrios Tsapetis
,
Michael D. Shields
,
Dimitris G. Giovanis
,
Audrey Olivier
,
Lukás Novák
,
Promit Chakroborty
,
Himanshu Sharma
,
Mohit Chauhan
,
Katiana Kontolati
,
Lohit Vandanapu
,
Dimitrios Loukrezis
,
Michael Gardner
UQpy v4.1: Uncertainty quantification with Python.
SoftwareX
24 (2023)
Somdatta Goswami
,
Katiana Kontolati
,
Michael D. Shields
,
George Em Karniadakis
Deep transfer operator learning for partial differential equations under conditional shift.
Nat. Mac. Intell.
4 (12) (2022)
Katiana Kontolati
,
Somdatta Goswami
,
Michael D. Shields
,
George Em Karniadakis
On the influence of over-parameterization in manifold based surrogates and deep neural operators.
CoRR
(2022)
Katiana Kontolati
,
Dimitrios Loukrezis
,
Dimitrios G. Giovanis
,
Lohit Vandanapu
,
Michael D. Shields
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems.
CoRR
(2022)
Katiana Kontolati
,
Dimitrios Loukrezis
,
Dimitrios G. Giovanis
,
Lohit Vandanapu
,
Michael D. Shields
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems.
J. Comput. Phys.
464 (2022)
Somdatta Goswami
,
Katiana Kontolati
,
Michael D. Shields
,
George Em Karniadakis
Deep transfer learning for partial differential equations under conditional shift with DeepONet.
CoRR
(2022)
Katiana Kontolati
,
Natalie Klein
,
Nishant Panda
,
Diane Oyen
Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra.
CoRR
(2021)
Katiana Kontolati
,
Dimitrios Loukrezis
,
Ketson R. M. dos Santos
,
Dimitrios G. Giovanis
,
Michael D. Shields
Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models.
CoRR
(2021)