Releases#

Version 0.3 (2025-07-15)#

  • Improve UMAP via direct gradient computation and edge masking PR #198.

  • Support for torch.compile PR #194.

  • Automatically handle duplicates PR #188.

  • Standardize logging PR #187.

  • Make affinity_out optional in AffinityMatcher PR #186.

  • Implement PHATE algorithm PR #185.

  • Implement PACMAP algorithm PR #182.

  • COSNE support for hyperbolic embeddings PR #178.

  • Allow for any Torch optimizer or scheduler PR #174.

  • Ensure compatibility with python 3.8+ PR #173.

Version 0.2 (2025-02-07)#

  • FAISS support for KNN PR #160.

  • CIFAR examples with DINOv2 features PR #158.

  • Fast linter and formatter with Ruff PR #151.

  • Pre-commit hooks added for code quality and consistency checks PR #147.

  • Incremental PCA PR #137.

  • Clean citation style via sphinxcontrib-bibtex PR #143.

  • Functionality to switch to keops backend if it is installed and an out-of-memory error is raised PR #130.

  • Code of conduct PR #127.

  • Pull request template PR #125.

Version 0.1 (2024-09-17)#

  • Multiple basic affinities, including scalar product, Gaussian, and Student kernels.

  • Affinities based on k-NN normalizations such as Self-tuning affinities and MAGIC.

  • Doubly stochastic affinities with entropic and quadratic projections.

  • Adaptive affinities with entropy control (entropic affinity) and its symmetric version.

  • Input and output affinities of UMAP.

  • A template object AffinityMatcher to solve DR with gradient descent and any input and output affinities.

  • Neighbor embedding methods like SNE, t-SNE, t-SNEkhorn, UMAP, LargeVis, and InfoTSNE.

  • Template objects for neighbor embedding methods.

  • Spectral embeddings via eigendecomposition of the input affinity matrix (when applicable).

  • KeOps compatibility for all components, except spectral embeddings.

  • Silhouette score.