| VB-DeepONet: A Bayesian operator learning framework for uncertainty quantification S Garg, S Chakraborty Engineering Applications of Artificial Intelligence 118, 105685, 2023 | 40* | 2023 |
| 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 | 36* | 2022 |
| 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 | 23 | 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 | 19 | 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 | 10 | 2023 |
| Digital Twin for Dynamical Systems T Tripura, S Garg, S Chakraborty Machine Learning in Modeling and Simulation: Methods and Applications, 255-296, 2023 | 4 | 2023 |
| Neuroscience inspired neural operator for partilial differential equations S Garg, S Chakraborty Journal of Computational Physics, 113266, 2024 | 3 | 2024 |
| Randomized prior wavelet neural operator for uncertainty quantification S Garg, S Chakraborty arXiv preprint arXiv:2302.01051, 2023 | 3 | 2023 |
| Neuroscience inspired scientific machine learning (Part-1): Variable spiking neuron for regression S Garg, S Chakraborty arXiv preprint arXiv:2311.09267, 2023 | 2 | 2023 |
| Hybrid variable spiking graph neural networks for energy-efficient scientific machine learning I Jain, S Garg, S Shriyam, S Chakraborty arXiv preprint arXiv:2412.09379, 2024 | | 2024 |
| Distribution free uncertainty quantification in neuroscience-inspired deep operators S Garg, S Chakraborty arXiv preprint arXiv:2412.09369, 2024 | | 2024 |
Souvik ChakrabortyAssistant Professor, IIT DelhiПодтвержден адрес электронной почты в домене am.iitd.ac.in