9 citations · 9 across the 3 of their papers we have counts for
3 papers
Parametric Interpolation of Dynamic Mode Decomposition for Predicting Nonlinear Systems
Ananda Chakrabarti, Haitham H. Saleh, Indranil Nayak +3
We present parameter-interpolated dynamic mode decomposition (piDMD), a parametric reduced-order modeling framework that embeds known parameter-affine structure directly into the D…
Temporally-Consistent Bilinearly Recurrent Autoencoders for Control Systems
Ananda Chakrabarti, Indranil Nayak, Debdipta Goswami
This paper introduces the temporally-consistent bilinearly recurrent autoencoder (tcBLRAN), a Koopman operator based neural network architecture for modeling a control-affine nonli…
Temporally Consistent Koopman Autoencoders for Forecasting Dynamical Systems
Indranil Nayak, Ananda Chakrabarty, Mrinal Kumar +2
Absence of sufficiently high-quality data often poses a key challenge in data-driven modeling of high-dimensional spatio-temporal dynamical systems. Koopman Autoencoders (KAEs) har…