9 citations · 9 across the 7 of their papers we have counts for
4 papers · 1 filter
CoNBONet: Conformalized Neuroscience-inspired Bayesian Operator Network for Reliability Analysis
Shailesh Garg, Souvik Chakraborty
Time-dependent reliability analysis of nonlinear dynamical systems under stochastic excitations is a critical yet computationally demanding task. Conventional approaches, such as M…
Distribution free uncertainty quantification in neuroscience-inspired deep operators
Shailesh Garg, Souvik Chakraborty
Energy-efficient deep learning algorithms are essential for a sustainable future and feasible edge computing setups. Spiking neural networks (SNNs), inspired from neuroscience, are…
Assessment of DeepONet for reliability analysis of stochastic nonlinear dynamical systems
Shailesh Garg, Harshit Gupta, Souvik Chakraborty
Time dependent reliability analysis and uncertainty quantification of structural system subjected to stochastic forcing function is a challenging endeavour as it necessitates consi…
Machine learning based digital twin for stochastic nonlinear multi-degree of freedom dynamical system
Shailesh Garg, Ankush Gogoi, Souvik Chakraborty +1
The potential of digital twin technology is immense, specifically in the infrastructure, aerospace, and automotive sector. However, practical implementation of this technology is n…