3D Data

SE(3)-equivariant networks are neural network architectures designed to respect the symmetries of the special Euclidean group SE(3), which combines 3D rotations and translations. These networks maintain equivariance under transformations in three-dimensional space, making them particularly useful in fields such as robotics, computer vision, and molecular modeling.