drewwilimitis / hyperbolic-learning
Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)
☆128Updated 4 years ago
Alternatives and similar repositories for hyperbolic-learning:
Users that are interested in hyperbolic-learning are comparing it to the libraries listed below
- Hyperbolic Hierarchical Clustering.☆197Updated last year
- Source code for the paper "Hyperbolic Neural Networks", https://arxiv.org/abs/1805.09112☆172Updated 4 years ago
- Hyperbolic PCA via Horospherical Projections☆69Updated last year
- Hyperbolic Embeddings☆377Updated last year
- code for "Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders".☆123Updated last year
- Hyperbolic Graph Neural Networks☆228Updated 5 years ago
- Topological Graph Neural Networks (ICLR 2022)☆119Updated 2 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆54Updated 3 years ago
- A Python package for intrinsic dimension estimation☆84Updated 5 months ago
- Hyperbolic Neural Networks, pytorch☆86Updated 5 years ago
- Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.☆141Updated 3 years ago
- Implementation of the "Poincare Glove: Hyperbolic word embeddings" paper☆85Updated 4 years ago
- Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Z…☆44Updated 4 years ago
- Learning Tree structures and Tree metrics☆23Updated 5 months ago
- Official implementation (learning part) for paper: Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models☆18Updated 5 months ago
- ☆79Updated 2 years ago
- Neural Graph Differential Equations (Neural GDEs)☆197Updated 3 years ago
- Graph Data Augmentation Library for PyTorch Geometric☆129Updated 2 years ago
- Poincaré Embedding☆40Updated 7 years ago
- Official PyTorch implementation of Hyperbolic Neural Networks++☆64Updated 3 years ago
- Code for Optimal Transport for structured data with application on graphs☆98Updated 2 years ago
- Library that contains implementations of machine learning components in the hyperbolic space☆132Updated 9 months ago
- Code for Graph Normalizing Flows.☆60Updated 5 years ago
- Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called si…☆76Updated 3 years ago
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆59Updated 3 years ago
- Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)☆193Updated 10 months ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆81Updated 4 months ago
- Deep Graph Mapper: Seeing Graphs through the Neural Lens☆55Updated last year
- Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R…☆131Updated 4 years ago
- Learning neural network embeddings in hyperbolic spaces☆14Updated 5 years ago