🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps
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Updated
May 13, 2024 - Python
🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
Pytorch implementation of Hyperspherical Variational Auto-Encoders
CellRank: dynamics from multi-view single-cell data
Tensorflow implementation of Hyperspherical Variational Auto-Encoders
TLDR is an unsupervised dimensionality reduction method that combines neighborhood embedding learning with the simplicity and effectiveness of recent self-supervised learning losses
Systematically learn and evaluate manifolds from high-dimensional data
Tensorflow implementation of adversarial auto-encoder for MNIST
Code for the NeurIPS'19 paper "Guided Similarity Separation for Image Retrieval"
Code and reuslts accompanying the NeurIPS 2022 paper with the title SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
This is the code implementation for the GMML algorithm.
Pytorch code for “Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment ” (DRMEA) (AAAI 2020).
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.
Code for WACV 2022 paper "Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation"
TensorFlow Implementation of Manifold Regularized Convolutional Neural Networks.
ManifoldEM Python suite
A simple library for t-SNE animation and a zoom-in feature to apply t-SNE in that region
We propose a density-based estimator for weighted geodesic distances suitable for data lying on a manifold of lower dimension than ambient space and sampled from a possibly nonuniform distribution
Implementation of Low Distortion Local Eigenmaps and several variations of it
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