2D visualizer for specular path manifolds

This repository implements a simpleVAE for training on CPU on the MNIST dataset and provides ability to visualize the latent space, entire manifold as well as visualize how numbers interpolate between each other.

Interactive visualization of Manifold-Constrained Hyper-Connections (mHC) for stable deep network training

Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning

IsUMap is a tool for manifold learning, dimension reduction and data visualization

Visualizes the Riemannian manifolds Solv/Sol, Nil, SL(2,R), H^3 and E^3 in real time using ray marching along geodesics.

Manifold, Clustering, Interactive visualization

Model-based deep hyperbolic manifold learning for visualizing complex hierarchical structures in single-cell genomics data

Implementation and visualization of 4 frequently used manifold learning algorithms (四种流形学习算法的实现及可视化)

Python script that implements a random forest algorithm to predict several ADME-Tox classifications of bioactive molecules accompanied with a visualization technique called Uniform Manifold Approximation Projection (UMAP) [1]. This work is an amalgamation of previous great work by fellow researchers [2-5] with an extension towards our own research on predicting molecular ion fragmentation by a mass spectrometer (MS). In particular, we investigated the impact of different molecular encodings on the algorithm's prediction accuracy, sensitivity and specificity.

A geometric "Vector Network Analyzer" for ComfyUI. Visualize latent trajectories, quantify convergence quality (Q-Score), and auto-tune parameters based on the Manifold Alignment Protocol (MAP).

SEMAFORE: SEmantic visualization with MAniFOld REgularization

A package for visualizing the information-geometric manifolds of statistical models and data.

A Manifold Alignment Approach for Hyperspectral Image Visualization With Natural Color.

Our web app provides a "No code. No installation" platform for researchers to upload images and compare clustering results with popular machine learning models and manifold learning algorithms, making experimenting and prototyping with ML less time-consuming. There’s currently no existing app that allows fast organization and visualization of data

Neuronal Spiking Ensembles: Dynamics of Representational Geometry. Explore manifold analysis and visualization of spiking ensemble dynamics during complex cognitive tasks.

Tools to simulate and visualize Brownian motion on manifolds

WebGPU mathematical surface visualizer rendering 25+ manifold types with WGSL compute shaders, real-time post-processing, and audio-reactive animations.

Mini-library for visualizing 2D manifolds in 3D space

A Typst package for visualizing Calabi-Yau manifolds using CeTZ 3D drawing primitives.

An interactive visualization of gradient, divergence, and curl. You may choose to trace gradient on static 3 dimensional manifold; or trace divergence and curl at arbitrary point in a motional vector field. Detailed explanation and calculations are equipped along visual explanations.

ArchR is a full-featured software suite for the analysis of single-cell chromatin accessibility data. Latch supports visualizing UMAPs from scATAC-seq data as well as peak browser tracks. In ArchR, embeddings, such as Uniform Manifold Approximation and Projection (UMAP) are used to visualize single cells in reduced dimension space. UMAP is designed to preserve both the local and most of the global structure in the data. Peak browser tracks are genome-track level visualizations of chromatin accessibility observed within groups of cells.

Visualizing model manifold for CMB, Ising, Trained Neural Network

Use Manifold Learning, Mapping and Discriminant Analysis to Visualize Image Datasets

Official Neurotopological Audit Dossier: SCDS-Phoenix raw logs and manifold state visualizations.

3D animated visualization of Calabi-Yau manifold by Python+Meshmixer+3D-viewer

Visualization of curved space manifold and metric tensor through normal Linear vector space

A program to compute and visualize the (un)stable manifold of a vector field.

Blind spatial manifold compression and 3D AR visualization for high-density neural probes (Neuralink N1).

A routine to sort high dimention data set using manifold learning and sorting for better visualization