Showing physics.comp-phShow all
2 papers · 1 filter
physics.comp-ph2026
SPINONet: Scalable Spiking Physics-informed Neural Operator for Computational Mechanics Applications
Shailesh Garg, Luis Mandl, Somdatta Goswami +1
Energy efficiency remains a critical challenge in deploying physics-informed operator learning models for computational mechanics and scientific computing, particularly in power-co…
physics.comp-ph2025
NeuroPINNs: Neuroscience Inspired Physics Informed Neural Networks
Shailesh Garg, Souvik Chakraborty
We introduce NeuroPINNs, a neuroscience-inspired extension of Physics-Informed Neural Networks (PINNs) that incorporates biologically motivated spiking neuron models to achieve ene…