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Proposes LieBN, a framework for batch normalization over Lie groups, applicable to SPD, rotation, and correlation manifolds, with theoretical guarantees and extensive experiments.
This paper proposes Lie group embedded dynamical neural networks (LieEDNN) with learning algorithms based on gradient descent and metric projection on smooth manifolds, enabling stable dynamics on Lie groups like SO(3) and SE(3) for robotics and control applications.