The Equivariant Point Networks part3(Machine Learning future) – Monodeep Mukherjee

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Summary

● Equivariance to permutations and rigid motions is important for 3D learning problems.
● The Equivariant Tensor Field Network architecture is universal and can approximate any equivariant function.
● The authors propose a simpler architecture with the same universality guarantees and evaluate its performance on Modelnet40.
● The code to reproduce the experiments is available on GitHub.

Author: Monodeep Mukherjee
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