e3nn: Euclidean Neural Networks. (arXiv:2207.09453v1 [cs.LG])

We present e3nn, a generalized framework for creating E(3) equivariant
trainable functions, also known as Euclidean neural networks. e3nn naturally
operates on geometry and geometric tensors that describe systems in 3D and
transform predictably under a change of coordinate system. The core of e3nn are
equivariant operations such as the TensorProduct class or the spherical
harmonics functions that can be composed to create more complex modules such as
convolutions and attention mechanisms. These core operations of e3nn can be
used to efficiently articulate Tensor Field Networks, 3D Steerable CNNs,
Clebsch-Gordan Networks, SE(3) Transformers and other E(3) equivariant
networks.

Source: https://arxiv.org/abs/2207.09453

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