27 citations · 81 across the 22 of their papers we have counts for
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cs.LG2018
geomstats: a Python Package for Riemannian Geometry in Machine Learning
Nina Miolane, Johan Mathe, Claire Donnat +2
We introduce geomstats, a python package that performs computations on manifolds such as hyperspheres, hyperbolic spaces, spaces of symmetric positive definite matrices and Lie gro…
cs.CV2018
Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry
Benjamin Hou, Nina Miolane, Bishesh Khanal +7
Pose estimation, i.e. predicting a 3D rigid transformation with respect to a fixed co-ordinate frame in, SE(3), is an omnipresent problem in medical image analysis with application…