mlsanityData to 7 Oct 2026

Manify: A Python Library for Learning Non-Euclidean Representations

arXiv 2503.09576 ↗First posted 12 Mar 2025cs.LGcited by 2

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Abstract (arXiv)

We present Manify, an open-source Python library for non-Euclidean representation learning. Leveraging manifold learning techniques, Manify provides tools for learning embeddings in (products of) non-Euclidean spaces, performing classification and regression with data that lives in such spaces, estimating the curvature of a manifold, and more. Manify aims to advance research and applications in machine learning by offering a comprehensive suite of tools for manifold-based data analysis. Our source code, examples, and documentation are available at https://github.com/pchlenski/manify.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 18 of its 32 references that are in the map. First posted on arXiv 12 Mar 2025.

Builds on

18 of 32 references.

References · 18

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  3. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  4. 2019Simplifying Graph Convolutional Networkscited by 1,470
  5. 2019Hyperbolic Graph Convolutional Neural Networkscited by 400
  6. 2018Hyperbolic Neural Networkscited by 393
  7. 2019Hyperbolic Graph Neural Networkscited by 244
  8. 2019Hyperbolic Image Embeddingscited by 219
  9. 2022Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Modelscited by 172
  10. 2019Constant Curvature Graph Convolutional Networkscited by 106
  11. 2019Mixed-curvature Variational Autoencoderscited by 85
  12. 2021Neural Distance Embeddings for Biological Sequencescited by 17
6 more
  1. 2023Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learningcited by 15
  2. 2021Linear Classifiers in Product Space Formscited by 11
  3. 2023Fast hyperboloid decision tree algorithmscited by 7
  4. 2023HypLL: The Hyperbolic Learning Librarycited by 6
  5. 2023Principal Component Analysis in Space Formscited by 5
  6. 2024Mixed-curvature decision trees and random forestscited by 2

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Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025Hyperbolic Genome Embeddingscited by 3
  2. 2025Even Faster Hyperbolic Random Forests: A Beltrami-Klein Wrapper Approachcited by 0