The Role of Symmetry Breaking in Machine Learning: A Study on Equivariant Functions and E-MLPs

Symmetry is a fundamental characteristic where an object remains unchanged under certain transformations and is a key inductive bias that enhances model performance and efficiency. Therefore, understanding and leveraging the concept of symmetry has emerged as a cornerstone for designing more efficient and effective neural network models. Researchers have consistently sought ways to exploit this […]

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