Search Results for author: Christian Shewmake

Found 2 papers, 2 papers with code

Bispectral Neural Networks

1 code implementation • 7 Sep 2022 • Sophia Sanborn, Christian Shewmake, Bruno Olshausen, Christopher Hillar

We present a neural network architecture, Bispectral Neural Networks (BNNs) for learning representations that are invariant to the actions of compact commutative groups on the space over which a signal is defined.

Adversarial Robustness Representation Learning

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Geomstats: A Python Package for Riemannian Geometry in Machine Learning

1 code implementation • ICLR 2019 • Nina Miolane, Alice Le Brigant, Johan Mathe, Benjamin Hou, Nicolas Guigui, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Bernhard Kainz, Claire Donnat, Susan Holmes, Xavier Pennec

We introduce Geomstats, an open-source Python toolbox for computations and statistics on nonlinear manifolds, such as hyperbolic spaces, spaces of symmetric positive definite matrices, Lie groups of transformations, and many more.

BIG-bench Machine Learning Clustering +2

1,148

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