google / quickshift
A clustering algorithm that first finds the high-density regions (cluster-cores) of the data and then clusters the remaining points by hill-climbing. Such seedings act as more stable and expressive cluster-cores than the singleton modes found by popular algorithm such as mean shift. (https://arxiv.org/abs/1805.07909)
☆68Updated 6 years ago
Alternatives and similar repositories for quickshift:
Users that are interested in quickshift are comparing it to the libraries listed below
- Easing non-convex optimization with neural networks.☆22Updated 6 years ago
- Morgan A. Schmitz., Matthieu Heitz, Nicolas Bonneel, Fred Ngole, David Coeurjolly, Marco Cuturi, Gabriel Peyré, and Jean-Luc Starck. "Was…☆18Updated 5 years ago
- stochs: fast stochastic solvers for machine learning in C++ and Cython☆26Updated 2 years ago
- Dirichlet Process K-means☆47Updated 9 months ago
- Code for "Fast Unbalanced Optimal Transport on a Tree" (NeurIPS 2020)☆13Updated 4 years ago
- Convenient hyperparameter optimization☆14Updated 11 months ago
- The Linear Information Sieve☆16Updated 7 years ago
- Code for our paper "CliqueCNN: Deep Unsupervised Exemplar Learning" https://arxiv.org/abs/1608.08792☆22Updated 7 years ago
- A Cython interface to FLANN☆24Updated 4 years ago
- A library for hypergraphs and hypergraph algorithms☆28Updated 9 years ago
- Soft Decision Trees (code for ICPR 21 paper)☆32Updated 11 years ago
- Python tools for Morse Smale Complex analysis and visualization☆10Updated 3 years ago
- Python implementation of cover trees, near-drop-in replacement for scipy.spatial.kdtree☆33Updated 13 years ago
- Implementation of Trimmed Grassmann Average (TGA) by Hauberg S et al. in Python☆23Updated 9 years ago
- 3D Roto-translation equivariant convolutions☆54Updated 6 years ago
- SGCRFpy: Sparse Gaussian Conditional Random Fields in Python☆29Updated 8 years ago
- Graph-based learning in Python☆18Updated 7 years ago
- ☆29Updated 11 months ago
- Code for Fast Information-theoretic Bayesian Optimisation☆16Updated 6 years ago
- Semi-Supervised t-SNE using a Bayesian prior based on partial labelling☆42Updated 8 years ago
- ☆13Updated 5 years ago
- MCMC for the Dark Energy Spectroscopic Instrument☆13Updated 8 years ago
- Examples of more involved applications using Geomstats☆32Updated 4 years ago
- Fork of cma-es library by Nikolaus Hansen☆11Updated 7 years ago
- Neighborhood Components Analysis in C++☆38Updated 15 years ago
- Computation using data flow graphs for scalable machine learning☆24Updated 6 years ago
- Experiments from the article "Tensorial Mixture Models"☆25Updated 6 years ago
- Rudi, A., Camoriano, R. and Rosasco, L., Less is more: Nyström computational regularization. In Advances in Neural Information Processing…☆12Updated 5 years ago
- ☆34Updated 7 years ago
- Fast, vectorized C++ implementation of K-Means using the Eigen matrix template library. Includes Matlab and Python interfaces.☆57Updated 7 years ago