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Tegan Emerson

2 accepted papers

2022

In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?

NeurIPS 2022accept

It is often said that a deep learning model is ``invariant'' to some specific type of transformation. However, what is meant by this statement strongly depends on the context in which it is made. In this paper we explore the nature of invariance and equivariance of deep learning models with the goal…

Cited by 17SourcePDFScholar
2022

On the Symmetries of Deep Learning Models and their Internal Representations

NeurIPS 2022accept

Symmetry has been a fundamental tool in the exploration of a broad range of complex systems. In machine learning, symmetry has been explored in both models and data. In this paper we seek to connect the symmetries arising from the architecture of a family of models with the symmetries of that family…

Cited by 45SourcePDFScholar