laplacian-eigenmaps

There are 15 repositories under laplacian-eigenmaps topic.

  • drewwilimitis/Manifold-Learning

    Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)

    Language:Jupyter Notebook2205637

  • davisidarta/fastlapmap

    Fast Laplacian Eigenmaps: lightweight multicore LE for non-linear dimensional reduction with minimal memory usage. Outperforms sklearn's implementation and escalates linearly beyond 10e6 samples.

    Language:Python22201

  • JAVI897/Laplacian-Eigenmaps

    Implemented Laplacian Eigenmaps

    Language:Jupyter Notebook18134

  • peterparity/conservation-laws-manifold-learning

    Discovering Conservation Laws using Optimal Transport and Manifold Learning

    Language:Jupyter Notebook16203

  • jzavatoneveth/laplacian-eigenmaps

    Spectral embedding using Laplacian Eigenmaps

    Language:Matlab15209

  • nileshkhetrapal/YassQueenDB

    Graph database library that allows you to store, analyze, and search through your data in a graph format. By using the Universal Sentence Encoder, it provides an efficient and semantic approach to handle text data. 📚🧠🚀

    Language:Python14290

  • PKU-ML/LaplacianCanonization

    Official code for NeurIPS 2023 paper "Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding".

    Language:Python7301

  • PyDimRed/PyDimRed

    A comparison between some dimension reduction algorithms

    Language:Jupyter Notebook5302

  • tejasnp163/Dimensionality-Reduction-on-Wine-Dataset

    Performed different tasks such as data preprocessing, cleaning, classification, and feature extraction/reduction on wine dataset.

    Language:Jupyter Notebook5200

  • jasonfilippou/DimReduce

    Implementations of 3 linear and non-linear dimensionality reduction algorithms

    Language:Python4201

  • GeorgeMLP/laplacian-canonization

    Official code for NeurIPS 2023 paper "Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding".

    Language:Python2200

  • msarrias/unsupervised-learning-algorithms

    Implement some dimensionality reduction and clustering methods and reproduce results from different papers. FLAME clustering, Laplacian Eigenmaps, Spectral clustering...

    Language:Jupyter Notebook2202

  • GeorgeMLP/basis-invariance-synthetic-experiment

    Basis invariance synthetic experiment in Appendix D of NeurIPS 2023 paper "Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding".

    Language:Python1100

  • jgurakuqi/graph-kernels-and-manifold-svm

    This project aims to compare the performance obtained using a linear Support Vector Machine model whose data was first processed through a Shortest Path kernel with the same SVM, this time with data also processed by two alternative Manifold Learning techniques: Isomap and Spectral Embedding.

    Language:Jupyter Notebook1100

  • arjunsawhney1/face-ML

    In this repo, I demonstrate how simple Linear Algebra concepts can be utilized for powerful image element detection applications

    Language:Jupyter Notebook0100