22 citations · 71 across the 11 of their papers we have counts for
11 papers
Discrete empirical interpolation in the tensor t-product framework
Sridhar Chellappa, Lihong Feng, Peter Benner
The discrete empirical interpolation method (DEIM) is a well-established approach, widely used for state reconstruction using sparse sensor/measurement data, nonlinear model reduct…
GS-PINN: Greedy Sampling for Parameter Estimation in Partial Differential Equations
Ali Forootani, Harshit Kapadia, Sridhar Chellappa +2
Partial differential equation parameter estimation is a mathematical and computational process used to estimate the unknown parameters in a partial differential equation model from…
GN-SINDy: Greedy Sampling Neural Network in Sparse Identification of Nonlinear Partial Differential Equations
Ali Forootani, Harshit Kapadia, Sridhar Chellappa +2
The sparse identification of nonlinear dynamical systems (SINDy) is a data-driven technique employed for uncovering and representing the fundamental dynamics of intricate systems b…
Fast and Reliable Reduced-Order Models for Cardiac Electrophysiology
Sridhar Chellappa, Barış Cansız, Lihong Feng +2
Mathematical models of the human heart are increasingly playing a vital role in understanding the working mechanisms of the heart, both under healthy functioning and during disease…
Accurate error estimation for model reduction of nonlinear dynamical systems via data-enhanced error closure
Sridhar Chellappa, Lihong Feng, Peter Benner
Accurate error estimation is crucial in model order reduction, both to obtain small reduced-order models and to certify their accuracy when deployed in downstream applications such…
Fast A Posteriori State Error Estimation for Reliable Frequency Sweeping in Microwave Circuits via the Reduced-Basis Method
Valentin de la Rubia, Sridhar Chellappa, Lihong Feng +1
We develop a compact, reliable model order reduction approach for fast frequency sweeps in microwave circuits by means of the reduced-basis method. Contrary to what has been previo…
Inf-Sup-Constant-Free State Error Estimator for Model Order Reduction of Parametric Systems in Electromagnetics
Sridhar Chellappa, Lihong Feng, Valentin de la Rubia +1
A reliable model order reduction process for parametric analysis in electromagnetics is detailed. Special emphasis is placed on certifying the accuracy of the reduced-order model.…
A Training Set Subsampling Strategy for the Reduced Basis Method
Sridhar Chellappa, Lihong Feng, Peter Benner
We present a subsampling strategy for the offline stage of the Reduced Basis Method. The approach is aimed at bringing down the considerable offline costs associated with using a f…
Adaptive Interpolatory MOR by Learning the Error Estimator in the Parameter Domain
Sridhar Chellappa, Lihong Feng, Valentin de la Rubia +1
Interpolatory methods offer a powerful framework for generating reduced-order models (ROMs) for non-parametric or parametric systems with time-varying inputs. Choosing the interpol…
Adaptive Basis Construction and Improved Error Estimation for Parametric Nonlinear Dynamical Systems
Sridhar Chellappa, Lihong Feng, Peter Benner
An adaptive scheme to generate reduced-order models for parametric nonlinear dynamical systems is proposed. It aims to automatize the POD-Greedy algorithm combined with empirical i…
An Adaptive Sampling Approach for the Reduced Basis Method
Sridhar Chellappa, Lihong Feng, Peter Benner
The offline time of the reduced basis method can be very long given a large training set of parameter samples. This usually happens when the system has more than two independent pa…