2 citations · 2 across the 2 of their papers we have counts for
2 papers
math.NA2024
Improving hp-Variational Physics-Informed Neural Networks for Steady-State Convection-Dominated Problems
Thivin Anandh, Divij Ghose, Himanshu Jain +3
This paper proposes and studies two extensions of applying hp-variational physics-informed neural networks, more precisely the FastVPINNs framework, to convection-dominated convect…
cs.LG2024★ 2 cited
FastVPINNs: Tensor-Driven Acceleration of VPINNs for Complex Geometries
Thivin Anandh, Divij Ghose, Himanshu Jain +1
Variational Physics-Informed Neural Networks (VPINNs) utilize a variational loss function to solve partial differential equations, mirroring Finite Element Analysis techniques. Tra…