Assessment of DeepONet for time dependent reliability analysis of dynamical systems subjected to stochastic loading S Garg, H Gupta, S Chakraborty Engineering Structures 270, 114811, 2022 | 27* | 2022 |
VB-DeepONet: A Bayesian operator learning framework for uncertainty quantification S Garg, S Chakraborty Engineering Applications of Artificial Intelligence 118, 105685, 2023 | 21* | 2023 |
Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systems S Garg, S Chakraborty, B Hazra Mechanical Systems and Signal Processing 173, 109039, 2022 | 17 | 2022 |
Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system S Garg, A Gogoi, S Chakraborty, B Hazra Probabilistic Engineering Mechanics 66, 103173, 2021 | 15 | 2021 |
Physics-integrated deep learning for uncertainty quantification and reliability estimation of nonlinear dynamical systems U Tripathi, S Garg, R Nayek, S Chakraborty Probabilistic Engineering Mechanics 72, 103419, 2023 | 6 | 2023 |
Randomized prior wavelet neural operator for uncertainty quantification S Garg, S Chakraborty arXiv preprint arXiv:2302.01051, 2023 | 2 | 2023 |
Digital Twin for Dynamical Systems T Tripura, S Garg, S Chakraborty Machine Learning in Modeling and Simulation: Methods and Applications, 255-296, 2023 | 1 | 2023 |
Neuroscience inspired scientific machine learning (Part-2): Variable spiking wavelet neural operator S Garg, S Chakraborty arXiv preprint arXiv:2311.14710, 2023 | | 2023 |
Neuroscience inspired scientific machine learning (Part-1): Variable spiking neuron for regression S Garg, S Chakraborty arXiv preprint arXiv:2311.09267, 2023 | | 2023 |