Prof. Sashikumaar Ganesan, Thivin Anandh and Divij Ghose presented their work on FastVPINNs at CRUNCH Lab Seminar held by Prof. George Karniadakis group on June 21-2024. Abstract for the Talk: Variational Physics-Informed Neural Networks (VPINNs) solve partial differential equations (PDEs)…
Our work on FastVPINNs for incompressible Navier-Stokes equation compiled by Thivin Anandh, Divij Ghose and Prof. Sashikumaar Ganesan was accepted for presentation at ICCFD’12 held at Kobe, Japan on Jul 17. Abstract of the Task: Physics-informed Neural Networks (PINNs) solve…
Mahesh Tom from AIReX lab completes his M.Tech research colloquium on “Learning Multiple Initial Conditions Using Physics-Informed Neural Networks (PINNs)”. The Abstract of his talk : Physics-Informed Neural Networks (PINNs) and their variants have emerged as tools for solving differential…