manifold-learning

Statistical Machine Intelligence & Learning Engine

🔴 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.

CellRank: dynamics from multi-view single-cell data

Pytorch implementation of Hyperspherical Variational Auto-Encoders

Single cell trajectory detection

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

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

Manifold-learning flows (ℳ-flows)

TorchDR - PyTorch Dimensionality Reduction

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

A Julia package for manifold learning and nonlinear dimensionality reduction

Tensorflow implementation of adversarial auto-encoder for MNIST

Data Science and Matrix Optimization course

A Framework for Dimensionality Reduction in R

This is the code implementation for the GMML algorithm.

Code for the NeurIPS'19 paper "Guided Similarity Separation for Image Retrieval"

A Python Library for Learning Non-Euclidean Representations