Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation
By James Townsend, Niklas Koep, Sebastian Weichwald. Journal of machine learning research, 2016
309 citations recorded by the source corpus.
Optimization on manifolds is a class of methods for optimization of an objective function, subject to constraints which are smooth, in the sense that the set of points which satisfy the constraints admits the structure of a differentiable manifold. While many optimization problems are of the described form, technicalities of differential geometry and the laborious calculation of derivatives pose a significant barrier for experimenting with these methods. We introduce Pymanopt (available at this https URL), a toolbox for optimization on manifolds, implemented in Python, that---similarly to the Manopt Matlab toolbox---implements several manifold geometries and optimization algorithms. Moreover, we lower the barriers to users further by using automated differentiation for calculating derivative information, saving users time and saving them from potential calculation and implementation errors.
Subfields: Biomedical Engineering, Computational Mechanics, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/0461e391cb2ef8c1f3deeb864efb30e7a1416622
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
In Computational Mechanics
In Statistics and Probability
- Rémi Flamary
- Nicolas Courty
- Ievgen Redko
- Alexandre Gramfort
- Andreas Mueller
- Aurélie Boisbunon
- Stanislas Chambon
- Danica J. Sutherland
Citations in the corpus
- POT: Python Optimal Transport (2021, methodology): “For some specific sub-modules such as dimensionality reduction with a Wasserstein loss, we used the manifold optimization library Pymanopt (Townsend et al., 2016) and the automatic differentiation library Autograd (Maclaurin et al., 2015).”
- Global rates of convergence for nonconvex optimization on manifolds (2016, unknown): “Software-wise, a few general toolboxes for optimization on manifolds exist now, e.g., Manopt (Boumal et al., 2014), PyManopt (Townsend et al., 2016) and ROPTLIB (Huang et al., 2016).”