Manify: A Python Library for Learning Non-Euclidean Representations

Fuente: arXiv
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Hauptverfasser: Chlenski, Philippe, Du, Kaizhu, Satow, Dylan, Khan, Raiyan R., Pe'er, Itsik
Format: Preprint
Veröffentlicht: 2025
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author Chlenski, Philippe
Du, Kaizhu
Satow, Dylan
Khan, Raiyan R.
Pe'er, Itsik
author_facet Chlenski, Philippe
Du, Kaizhu
Satow, Dylan
Khan, Raiyan R.
Pe'er, Itsik
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2503_09576
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Manify: A Python Library for Learning Non-Euclidean Representations
Chlenski, Philippe
Du, Kaizhu
Satow, Dylan
Khan, Raiyan R.
Pe'er, Itsik
Machine Learning
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.
title Manify: A Python Library for Learning Non-Euclidean Representations
topic Machine Learning
url https://arxiv.org/abs/2503.09576