Manify: A Python Library for Learning Non-Euclidean Representations
This is an incremental contribution that provides a comprehensive suite of tools for researchers and practitioners working with manifold-based data analysis in machine learning.
The authors tackled the problem of non-Euclidean representation learning by developing Manify, a Python library that provides tools for learning embeddings, performing classification and regression, and estimating curvature in non-Euclidean spaces, resulting in an open-source resource with available code and documentation.
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.