34 citations · 82 across the 15 of their papers we have counts for
4 papers · 1 filter
Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression
Tong Ma, Renke Huang, David Barajas-Solano +2
We propose a new forecasting method for predicting load demand and generation scheduling. Accurate week-long forecasting of load demand and optimal power generation is critical for…
Conditional Karhunen-Loève expansion for uncertainty quantification and active learning in partial differential equation models
Ramakrishna Tipireddy, David A Barajas-Solano, Alexandre M. Tartakovsky
We use a conditional Karhunen-Loève (KL) model to quantify and reduce uncertainty in a stochastic partial differential equation (SPDE) problem with partially-known space-dependent…
Solvers and precondtioners based on Gauss-Seidel and Jacobi algorithms for non-symmetric stochastic Galerkin system of equations
Ramakrishna Tipireddy, Eric T. Phipps, Roger G. Ghanem
In this work, solvers and preconditioners based on Gauss-Seidel and Jacobi algorithms are explored for stochastic Galerkin discretization of partial differential equations (PDEs) w…
A comparative study of physics-informed neural network models for learning unknown dynamics and constitutive relations
Ramakrishna Tipireddy, Paris Perdikaris, Panos Stinis +1
We investigate the use of discrete and continuous versions of physics-informed neural network methods for learning unknown dynamics or constitutive relations of a dynamical system.…