Publications
ArXiv pre-prints
Generative adversarial wavelet neural operator: Application to fault detection and isolation of multivariate time series data. [Paper]
Multi-fidelity wavelet neural operator with application to uncertainty quantification. [Paper]
A Bayesian framework for discovering interpretable Lagrangian of dynamical systems from data. [Paper]
A foundational neural operator that continuously learns without forgetting. [Paper]
Published Articles
2023
Deep neural operators can predict the real-time response of floating offshore structures under irregular waves. [Paper]
A sparse Bayesian framework for discovering interpretable nonlinear stochastic dynamical systems with Gaussian white noise. [Paper]
Wavelet neural operator: a neural operator for parametric partial differential equations. [Paper]
A wavelet neural operator based elastography for localization and quantification of tumors. [Paper]
Discovering stochastic partial differential equations from limited data using variational Bayes inference. [Paper]
Discovering interpretable Lagrangian of dynamical systems from data. [Paper]
Probabilistic machine learning based predictive and interpretable digital twin for dynamical systems. [Paper]
Fault detection and isolation using probabilistic wavelet neural operator auto-encoder with application to dynamic processes. [Paper]
MAntRA: A framework for model agnostic reliability analysis. [Paper]
A Bayesian framework for learning governing partial differential equation from data. [Paper]
2020
An Ito–Taylor weak 3.0 method for stochastic dynamics of nonlinear systems. [Paper]
Real time structural modal identification using recursive canonical correlation analysis and application towards online structural damage detection. [Paper]
Robust linear and nonlinear structural damage detection using recursive canonical correlation analysis. [Paper]