David A. Barajas-Solano

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 17

Top Topics

Gaussian Process

Data Assimilation

Active Learning

Top Venues

J. Comput. Phys.

SIAM/ASA J. Uncertain. Quantification

Multiscale Model. Simul.

Publications

Yu-Hong Yeung, David A. Barajas-Solano, Alexandre M. Tartakovsky
Gaussian process regression and conditional Karhunen-Loève models for data assimilation in inverse problems. J. Comput. Phys. 502 (2024)
Yu-Hong Yeung, Ramakrishna Tipireddy, David A. Barajas-Solano, Alexandre M. Tartakovsky
Conditional Korhunen-Loéve regression model with Basis Adaptation for high-dimensional problems: uncertainty quantification and inverse modeling. CoRR (2023)
Yu-Hong Yeung, David A. Barajas-Solano, Alexandre M. Tartakovsky
Gaussian process regression and conditional Karhunen-Loéve models for data assimilation in inverse problems. CoRR (2023)
Jacob Roth, David A. Barajas-Solano, Panos Stinis, Jonathan Weare, Mihai Anitescu
A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure. Multiscale Model. Simul. 19 (1) (2021)
Alexandre M. Tartakovsky, David A. Barajas-Solano, QiZhi He
Physics-informed machine learning with conditional Karhunen-Loève expansions. J. Comput. Phys. 426 (2021)
Yu-Hong Yeung, David A. Barajas-Solano, Alexandre M. Tartakovsky
Physics-Informed Machine Learning Method for Large-Scale Data Assimilation Problems. CoRR (2021)
Ramakrishna Tipireddy, David A. Barajas-Solano, Alexandre M. Tartakovsky
Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models. J. Comput. Phys. 418 (2020)
David A. Barajas-Solano, Alexandre M. Tartakovsky
Approximate Bayesian model inversion for PDEs with heterogeneous and state-dependent coefficients. J. Comput. Phys. 395 (2019)
Xiu Yang, David A. Barajas-Solano, Guzel Tartakovsky, Alexandre M. Tartakovsky
Physics-informed CoKriging: A Gaussian-process-regression-based multifidelity method for data-model convergence. J. Comput. Phys. 395 (2019)
Liu Yang, Prabhat, George E. Karniadakis, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston
Highly-Ccalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs. DLS@SC (2019)
Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston, Prabhat, George E. Karniadakis
Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs. CoRR (2019)
Jacob Roth, David A. Barajas-Solano, Panagiotis Stinis, Jonathan Weare, Mihai Anitescu
A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure. CoRR (2019)
Tong Ma, Renke Huang, David A. Barajas-Solano, Ramakrishna Tipireddy, Alexandre M. Tartakovsky
Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression. CoRR (2019)
David A. Barajas-Solano, Alexandre M. Tartakovsky
Probability and Cumulative Density Function Methods for the Stochastic Advection-Reaction Equation. SIAM/ASA J. Uncertain. Quantification 6 (1) (2018)
Xiu Yang, David A. Barajas-Solano, Guzel Tartakovsky, Alexandre M. Tartakovsky
Physics-Informed CoKriging: A Gaussian-Process-Regression-Based Multifidelity Method for Data-Model Convergence. CoRR (2018)
David A. Barajas-Solano, Alexandre M. Tartakovsky
Hybrid Multiscale Finite Volume Method for Advection-Diffusion Equations Subject to Heterogeneous Reactive Boundary Conditions. Multiscale Model. Simul. 14 (4) (2016)
David A. Barajas-Solano, Daniel M. Tartakovsky
Stochastic Collocation Methods for Nonlinear Parabolic Equations with Random Coefficients. SIAM/ASA J. Uncertain. Quantification 4 (1) (2016)
Peng Wang, David A. Barajas-Solano, Emil M. Constantinescu, Shrirang Abhyankar, Debojyoti Ghosh, Barry F. Smith, Zhenyu Huang, Alexandre M. Tartakovsky
Probabilistic Density Function Method for Stochastic ODEs of Power Systems with Uncertain Power Input. SIAM/ASA J. Uncertain. Quantification 3 (1) (2015)