TorchDR - PyTorch Dimensionality Reduction
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Updated
Jun 17, 2024 - Python
TorchDR - PyTorch Dimensionality Reduction
[IEEE CISS 2024, ICMLW 2023] Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy
🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps
This is the code implementation for the GMML algorithm.
CellRank: dynamics from multi-view single-cell data
Implementation of Low Distortion Local Eigenmaps and several variations of it
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
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…
A Python implementation of Manifold Sculpting
Extended Dynamic Mode Decomposition for system identification from time series data (with dictionary learning, control and streaming options). Diffusion Maps to extract geometric description from data.
topological deep learning
PyTorch implementation of Bezier simplex fitting
Monitoring of direct energy deposition process using deep-net based manifold learning and co-axial melt pool imaging
Systematically learn and evaluate manifolds from high-dimensional data
A reciprocal variant of Isomap for robust non-linear dimensionality reduction in Python
[ECML-PKDD 2021] Invertible Manifold Learning for Dimension Reduction
Shortest-Path Kernel analysis with LLE and Isomap manifold algorithms application
Here is where I will put all the code I use to generate my explanatory videos!
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