Statistical Machine Intelligence & Learning Engine

visualization nlp data-science machine-learning statistics computer-vision deep-learning clustering interpolation genetic-algorithm linear-algebra regression nearest-neighbor-search classification wavelet dataframe computer-algebra-system manifold-learning multidimensional-scaling llm

• Updated Nov 12, 2026
• Java

🔴 MiniSom is a minimalistic implementation of the Self Organizing Maps

machine-learning clustering som neural-networks dimensionality-reduction outlier-detection kohonen unsupervised-learning manifold-learning self-organizing-map vector-quantization

• Updated Oct 19, 2026
• Python

PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.

data-visualization dimensionality-reduction unsupervised-learning single-cell manifold-learning

• Updated Mar 4, 2026
• Python

CellRank: dynamics from multi-view single-cell data

data-science machine-learning bioinformatics genetics trajectory-generation markov-chains manifold-learning single-cell-genomics single-cell-rna-seq cell-fate-transitions fuzzy-clustering-analyses rna-velocity cell-fate-determination

• Updated Nov 4, 2026
• Python

Pytorch implementation of Hyperspherical Variational Auto-Encoders

machine-learning deep-learning pytorch vae manifold-learning variational-autoencoder von-mises-fisher hyperspherical-vae

• Updated Mar 21, 2020
• Python

Single cell trajectory detection

markov-chain dimensionality-reduction scrna-seq trajectory-generation diffusion-maps differentiation manifold-learning single-cell-genomics cell-fate-transitions scrna-seq-analysis

• Updated Nov 3, 2026
• Jupyter Notebook

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

python dimensionality-reduction manifold-learning isomap multidimensional-scaling spectral-embedding laplacian-eigenmaps locally-linear-embedding

• Updated Mar 5, 2020
• Jupyter Notebook

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

machine-learning deep-learning tensorflow vae manifold-learning variational-autoencoder von-mises-fisher hyperspherical-vae

• Updated Dec 1, 2018
• Python

Manifold-learning flows (ℳ-flows)

manifold-learning density-estimation normalizing-flows notagan

• Updated Nov 13, 2020
• Jupyter Notebook

TorchDR - PyTorch Dimensionality Reduction

python data-science cuda pytorch embeddings dimensionality-reduction tsne manifold-learning umap large-scale multi-gpu optimal-transport similarity-search spectral-embedding embedding-evaluation data-vizualisation neighbor-embedding affinity-matrix

• Updated Oct 27, 2026
• Python

python vae pycharm pitch manifold-learning variational-autoencoder world-vocoder manifold-vocoder

• Updated Dec 20, 2023
• Python

TLDR is an unsupervised dimensionality reduction method that combines neighborhood embedding learning with the simplicity and effectiveness of recent self-supervised learning losses

dimensionality-reduction manifold-learning unsupervised-machine-learning pytorch-implementation

• Updated Jun 15, 2022
• Python

[𝗜𝗖𝗠𝗟 𝟮𝟬𝟮𝟲] Dispersion loss counteracts embedding condensation and improves generalization in small language models

dispersion cosine-similarity embedding manifold-learning icml condensation latent-space pre-training embedding-vectors dispersive large-language-models llm geometric-learning llms llm-training small-language-models mid-training icml-2026 embedding-condensation

• Updated Jun 21, 2026
• Python

Systematically learn and evaluate the latent geometry of high-dimensional data, with a focus on scRNAseq analysis

visualization data-science machine-learning graph clustering scikit-learn data-visualization dimensionality-reduction single-cell graph-layout manifold-learning scrnaseq laplace-beltrami hypothesis-generation scrnaseq-analysis

• Updated Oct 4, 2026
• Python

Pure MLX implementations of UMAP, t-SNE, PaCMAP, TriMap, DREAMS, CNE, MMAE, and NNDescent for Apple Silicon. Metal GPU for computation and video rendering.

visualization machine-learning metal gpu numpy autoencoder dimensionality-reduction tsne embedding manifold-learning umap dreams mlx cne trimap nndescent mmae apple-silicon pacmap

• Updated Mar 20, 2026
• Python

A Julia package for manifold learning and nonlinear dimensionality reduction

julia dimensionality-reduction lle diffusion-maps manifold-learning isomap

• Updated Mar 2, 2024
• Julia

Tensorflow implementation of adversarial auto-encoder for MNIST

tensorflow gan mnist autoencoder vae manifold adversarial-networks manifold-learning adversarial-autoencoders aae

• Updated Nov 7, 2017
• Python

This is the code implementation for the GMML algorithm.

ai gradient manifold-learning beamforming meta-learning reconfigurable-intelligent-surfaces

• Updated Nov 29, 2024
• Python

A computational method to rank and infer drug-responsive cell population towards in-silico drug perturbation using a target-perturbed gene regulatory network (tpGRN) for single-cell transcriptomic data

single-cell manifold-learning gene-network drug-response cell-type-prioritization

• Updated Oct 16, 2025
• R

A Python Library for Learning Non-Euclidean Representations

machine-learning pytorch manifold-learning non-euclidean-geometry

• Updated Jul 29, 2026
• Jupyter Notebook