A simple library for t-SNE animation and a zoom-in feature to apply t-SNE in that region
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Updated
Jun 4, 2018 - Python
A simple library for t-SNE animation and a zoom-in feature to apply t-SNE in that region
Reconstructing the topology of a metric graph
Showcasing Manifold Learning with ISOMAP, and compare the model to other transformations, such as PCA and MDS.
Manifold mapping with ISOMAP (MATLAB).
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.
The goal here is to use a graph kernel and a manifold learning technique in conjunction with Support Vector Machines to enhance the SVM classification.
Multi-omics image alignment and analysis by information manifolds (MIAAIM)
Dimensionality reduction and data embedding via PCA, MDS, and Isomap.
Pipeline Consisting of LSTM + Variational and Transformer Based Autoencoders + PCA/UMAP (Parameterized and Non-Parameterized) For Generating Low-Dim Manifold Representation of V1 Neural Activity
Filling the 3D 'scattering volume' by appropriately-oriented 2D scattering patterns. An analytical model suggests a numerical procedure (using Diffusion Map and the fisrt 9 non-trivial eigenvectors). The Matlab code here 1) synthesizes 2D scattering patterns; 2) Forms the Distance Matrix of mimages; and 3) retrieves the (relative) orientations u…
Machiene Learning and Application module open assessment
A prior learning and sampling model informed tool for learning with Single Cell RNA-Seq data
Manifolds for Extreme-scale Applied Data Science
The code for Quantile-Quantile Embedding (QQE).
An investigation into Manifold Learning and MLPs on the sonar dataset
Linear and nonlinear dimensionality reduction and manifold learning.
Some knowledge about manifolds
A reciprocal variant of Isomap for robust non-linear dimensionality reduction in Python
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