Spiking recurrent neural networks for neuromorphic computing in nonlinear structural mechanics
SB Tandale, M Stoffel - Computer Methods in Applied Mechanics and …, 2023 - Elsevier
The present study aims to introduce an AI algorithm suitable for neuromorphic computing to
solve Boundary Value Problems in Engineering Mechanics. Following the trend of …
solve Boundary Value Problems in Engineering Mechanics. Following the trend of …
Neuroscience inspired neural operator for partial differential equations
S Garg, S Chakraborty - Journal of Computational Physics, 2024 - Elsevier
We propose, in this paper, a Variable Spiking Wavelet Neural Operator (VS-WNO), which
aims to bridge the gap between theoretical and practical implementation of Artificial …
aims to bridge the gap between theoretical and practical implementation of Artificial …
An efficient intrusion detection model based on convolutional spiking neural network
Many intrusion detection techniques have been developed to ensure that the target system
can function properly under the established rules. With the booming Internet of Things (IoT) …
can function properly under the established rules. With the booming Internet of Things (IoT) …
Brain-inspired spiking neural networks in Engineering Mechanics: a new physics-based self-learning framework for sustainable Finite Element analysis
SB Tandale, M Stoffel - Engineering with Computers, 2024 - Springer
The present study aims to develop a sustainable framework employing brain-inspired neural
networks for solving boundary value problems in Engineering Mechanics. Spiking neural …
networks for solving boundary value problems in Engineering Mechanics. Spiking neural …
Neuroscience inspired scientific machine learning (Part-1): Variable spiking neuron for regression
S Garg, S Chakraborty - arXiv preprint arXiv:2311.09267, 2023 - arxiv.org
Redundant information transfer in a neural network can increase the complexity of the deep
learning model, thus increasing its power consumption. We introduce in this paper a novel …
learning model, thus increasing its power consumption. We introduce in this paper a novel …
Neuroscience inspired scientific machine learning (Part-2): Variable spiking wavelet neural operator
S Garg, S Chakraborty - arXiv preprint arXiv:2311.14710, 2023 - arxiv.org
We propose, in this paper, a Variable Spiking Wavelet Neural Operator (VS-WNO), which
aims to bridge the gap between theoretical and practical implementation of Artificial …
aims to bridge the gap between theoretical and practical implementation of Artificial …
[PDF][PDF] Sustainable brain-inspired networks and deep-learning methods in structural mechanics
SB Tandale - researchgate.net
In computational mechanics, the Finite Element Method (FEM) has proven to be a popular
tool for analyzing complex structures in engineering applications. It offers tremendous …
tool for analyzing complex structures in engineering applications. It offers tremendous …