Katiana Kontolati

According to our database, Katiana Kontolati authored at least 8 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

UQpy v4.1: Uncertainty quantification with Python.

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

SoftwareX, December, 2023

On the influence of over-parameterization in manifold based surrogates and deep neural operators.

Katiana Kontolati, Somdatta Goswami, Michael D. Shields, George Em Karniadakis

J. Comput. Phys., April, 2023

Learning in latent spaces improves the predictive accuracy of deep neural operators.

Katiana Kontolati, Somdatta Goswami, George Em Karniadakis, Michael D. Shields

CoRR, 2023

2022

Deep transfer operator learning for partial differential equations under conditional shift.

Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis

Nat. Mac. Intell., December, 2022

A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems.

Katiana Kontolati, Dimitrios Loukrezis, Dimitrios G. Giovanis, Lohit Vandanapu, Michael D. Shields

J. Comput. Phys., 2022

Deep transfer learning for partial differential equations under conditional shift with DeepONet.

Somdatta Goswami, Katiana Kontolati, Michael D. Shields, George Em Karniadakis

CoRR, 2022

2021

Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra.

Katiana Kontolati, Natalie Klein, Nishant Panda, Diane Oyen

CoRR, 2021

Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models.

Katiana Kontolati, Dimitrios Loukrezis, Ketson R. M. dos Santos, Dimitrios G. Giovanis, Michael D. Shields

CoRR, 2021