440 citations · 851 across the 27 of their papers we have counts for
3 papers · 1 filter
Physics-informed Neural Networks (PINNs) for Wave Propagation and Full Waveform Inversions
Majid Rasht-Behesht, Christian Huber, Khemraj Shukla +1
We propose a new approach to the solution of the wave propagation and full waveform inversions (FWIs) based on a recent advance in deep learning called Physics-Informed Neural Netw…
Parallel Physics-Informed Neural Networks via Domain Decomposition
Khemraj Shukla, Ameya D. Jagtap, George Em Karniadakis
We develop a distributed framework for the physics-informed neural networks (PINNs) based on two recent extensions, namely conservative PINNs (cPINNs) and extended PINNs (XPINNs),…
A physics-informed neural network for quantifying the microstructure properties of polycrystalline Nickel using ultrasound data
Khemraj Shukla, Ameya D. Jagtap, James L. Blackshire +2
We employ physics-informed neural networks (PINNs) to quantify the microstructure of a polycrystalline Nickel by computing the spatial variation of compliance coefficients (compres…