mlsanityData to 7 Oct 2026

tensorflow-riemopt: A Library for Optimization on Riemannian Manifolds

arXiv 2105.13921 ↗First posted 27 May 2021cs.MS cs.CG cs.LGcited by 5

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Abstract (arXiv)

This paper presents tensorflow-riemopt, a Python library for geometric machine learning in TensorFlow. The library provides efficient implementations of neural network layers with manifold-constrained parameters, geometric operations on Riemannian manifolds, and stochastic optimization algorithms for non-Euclidean spaces. Designed for integration with TensorFlow Extended, it supports both research prototyping and production deployment of machine learning pipelines. The code and documentation are distributed under the MIT license and available at https://github.com/master/tensorflow-riemopt

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 22 of its 46 references that are in the map. First posted on arXiv 27 May 2021.

Builds on

22 of 46 references.

References · 22

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10 more
  1. 2020Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transformcited by 79
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Built on by

Cited by year

Citing papers per year: 2022: 3; 2023: 1; 2024: 0; 2025: 1.

5 papers.

  1. 2022Riemannian Hamiltonian methods for min-max optimization on manifoldscited by 12
  2. 2022Differentially Private Fr'echet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with log-Euclidean Metriccited by 8
  3. 2025Riemannian Optimization on Relaxed Indicator Matrix Manifoldcited by 5
  4. 2022Rieoptax: Riemannian Optimization in JAXcited by 1
  5. 2023Tame Riemannian Stochastic Approximationcited by 0