SE3 Equivariant Hemodynamic Field Estimation in 3D Artery Models via Graph Neural Networks
Offered By: Conference GSI via YouTube
Course Description
Overview
Explore a cutting-edge approach to hemodynamic field estimation in 3D artery models through a 20-minute conference talk at GSI. Delve into the application of SE3 equivariant graph neural networks for accurate and efficient blood flow predictions in complex arterial structures. Gain insights into how this innovative technique leverages geometric deep learning to enhance computational fluid dynamics simulations in cardiovascular research and clinical applications.
Syllabus
SE3 equivariant hemodynamic field estimation in 3D artery models via graph neural networks
Taught by
Conference GSI
Related Courses
Foundation of Computational Fluid DynamicsIndian Institute of Technology Madras via Swayam Computational Fluid Dynamics
Indian Institute of Technology Madras via Swayam A Hands-on Introduction to Engineering Simulations
Cornell University via edX Computational Fluid Dynamics For Incompressible Flows
Indian Institute of Technology Guwahati via Swayam Hydraulic Engineering
Indian Institute of Technology, Kharagpur via Swayam