drewwilimitis / Manifold-LearningLinks
Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)
☆233Updated 5 years ago
Alternatives and similar repositories for Manifold-Learning
Users that are interested in Manifold-Learning are comparing it to the libraries listed below
Sorting:
- Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.☆150Updated 3 years ago
- Materials of the Nordic Probabilistic AI School 2021.☆93Updated 3 years ago
- GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021☆51Updated 3 years ago
- Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)☆136Updated 5 years ago
- Implementation of the PersLay layer for persistence diagrams☆81Updated last year
- Embed strange attractors using a regularizer for autoencoders☆133Updated 4 years ago
- Estimators for the entropy and other information theoretic quantities of continuous distributions☆141Updated last year
- A set of jupyter notebooks for the practice of TDA with the python Gudhi library together with popular machine learning and data sciences…☆415Updated 3 months ago
- Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model☆101Updated 8 months ago
- Materials of the Nordic Probabilistic AI School 2022.☆181Updated 2 years ago
- A Python package for intrinsic dimension estimation☆91Updated 2 months ago
- Worked examples about manifold learning using sklearn and jupyter☆51Updated 6 years ago
- ☆152Updated 2 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆451Updated 10 months ago
- Gaussian Processes and Statistical Decision-making in Non-Euclidean Spaces☆199Updated 3 years ago
- Python package for graph-based clustering and semi-supervised learning☆94Updated 3 months ago
- A library for optimization on Riemannian manifolds☆110Updated 2 months ago
- A topological machine learning framework based on PyTorch☆183Updated last week
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆170Updated 3 years ago
- A curated list of topological data analysis (TDA) resources and links.☆201Updated 9 months ago
- Materials of the Nordic Probabilistic AI School 2023.☆90Updated last year
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆55Updated 4 years ago
- Distances and representations of persistence diagrams☆131Updated 3 months ago
- A short tutorial on implementing Canonical Polyadic (CP) tensor decomposition in Python☆64Updated last year
- Algorithms for computations on random manifolds made easier☆90Updated last year
- Simplicial neural networks (SNNs), a generalization of graph neural networks to data that live on a class of topological spaces called si…☆80Updated 4 years ago
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆60Updated 4 years ago
- Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data☆216Updated 3 years ago
- Manifold-learning flows (ℳ-flows)☆230Updated 4 years ago
- ☆241Updated 2 years ago