Search Results for author: Mikael Jorda

Found 2 papers, 2 papers with code

UniGrasp: Learning a Unified Model to Grasp with Multifingered Robotic Hands

1 code implementation24 Oct 2019 Lin Shao, Fabio Ferreira, Mikael Jorda, Varun Nambiar, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Oussama Khatib, Jeannette Bohg

The majority of previous work has focused on developing grasp methods that generalize over novel object geometry but are specific to a certain robot hand.

geomstats: a Python Package for Riemannian Geometry in Machine Learning

2 code implementations ICLR 2019 Nina Miolane, Johan Mathe, Claire Donnat, Mikael Jorda, Xavier Pennec

This paper also presents a review of manifolds in machine learning and an overview of the geomstats package with examples demonstrating its use for efficient and user-friendly Riemannian geometry.

Riemannian optimization

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