manifold-learning

There are 13 repositories under manifold-learning topic.

haifengl / smile
Statistical Machine Intelligence & Learning Engine
classification clustering computer-algebra-system computer-vision data-science dataframe deep-learning genetic-algorithm interpolation linear-algebra llm machine-learning manifold-learning multidimensional-scaling nearest-neighbor-search nlp regression statistics visualization wavelet
Language:Java 6000
JustGlowing / minisom
:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
machine-learning vector-quantization som neural-networks unsupervised-learning manifold-learning self-organizing-map clustering outlier-detection dimensionality-reduction kohonen
Language:Python 1422
KrishnaswamyLab / PHATE
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
single-cell dimensionality-reduction data-visualization unsupervised-learning manifold-learning
Language:Python 460
nicola-decao / s-vae-pytorch
Pytorch implementation of Hyperspherical Variational Auto-Encoders
pytorch vae variational-autoencoder von-mises-fisher machine-learning deep-learning manifold-learning hyperspherical-vae
Language:Python 345
cellrank
theislab / cellrank
CellRank: dynamics from multi-view single-cell data
machine-learning single-cell-rna-seq bioinformatics rna-velocity markov-chains genetics data-science fuzzy-clustering-analyses manifold-learning single-cell-genomics trajectory-generation cell-fate-transitions cell-fate-determination
Language:Python 337
johannbrehmer / manifold-flow
Manifold-learning flows (ℳ-flows)
notagan normalizing-flows manifold-learning density-estimation
Language:Jupyter Notebook 230
nicola-decao / s-vae-tf
Tensorflow implementation of Hyperspherical Variational Auto-Encoders
tensorflow vae von-mises-fisher machine-learning deep-learning manifold-learning variational-autoencoder hyperspherical-vae
Language:Python 223
drewwilimitis / Manifold-Learning
Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)
dimensionality-reduction isomap laplacian-eigenmaps locally-linear-embedding manifold-learning multidimensional-scaling python spectral-embedding
Language:Jupyter Notebook 214
dpeerlab / Palantir
Single cell trajectory detection
scrna-seq scrna-seq-analysis manifold-learning dimensionality-reduction diffusion-maps markov-chain differentiation single-cell-genomics trajectory-generation cell-fate-transitions
Language:Jupyter Notebook 209
tuanad121 / Python-WORLD
pitch python pycharm vae variational-autoencoder manifold-learning world-vocoder manifold-vocoder
Language:Python 149
naver / tldr
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 pytorch-implementation unsupervised-machine-learning
Language:Python 123
davisidarta / topometry
Systematically learn and evaluate manifolds from high-dimensional data
clustering data-visualization dimensionality-reduction graph graph-layout hypothesis-generation laplace-beltrami machine-learning manifold-learning scikit-learn single-cell data-science visualization
Language:Python 93
wildart / ManifoldLearning.jl
A Julia package for manifold learning and nonlinear dimensionality reduction
diffusion-maps dimensionality-reduction isomap julia lle manifold-learning
Language:Julia 92
hwalsuklee / tensorflow-mnist-AAE
Tensorflow implementation of adversarial auto-encoder for MNIST
tensorflow autoencoder adversarial-networks adversarial-autoencoders aae mnist vae gan manifold-learning manifold
Language:Python 86
gdkrmr / dimRed
A Framework for Dimensionality Reduction in R
dimensionality-reduction manifold-learning framework r visualization high-dimensional-data quality-control
Language:R 73
zhanglabtools / DSMO.course
Data Science and Matrix Optimization course
data-science matrix-factorization course-materials subspace-clustering matrix-completion manifold-alignment manifold-learning precision-matrix-estimation
70
layer6ai-labs / GSS
Code for the NeurIPS'19 paper "Guided Similarity Separation for Image Retrieval"
neurips image-retrieval manifold-learning gcn neurips-2019
Language:Python 64
kisungyou / Rdimtools
Dimension Reduction and Estimation Methods
manifold-learning dimension-reduction dimension-estimation subspace-learning r
Language:R 51
rkobler / TSMNet
Code and reuslts accompanying the NeurIPS 2022 paper with the title SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
bci brain-computer-interface eeg electroencephalography geometric-deep-learning machine-learning manifold-learning transfer-learning unsupervised-domain-adaptation
Language:Python 45
FenghaoZhu / GMML
This is the code implementation for the GMML algorithm.
ai beamforming gradient manifold-learning meta-learning reconfigurable-intelligent-surfaces
Language:Python 44
caltech_birds
ecm200 / caltech_birds
A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.
classification-model pytorch-tutorial cub-200-2011 feature-attribution activation-maximization manifold-learning caltech-birds deep-neural-networks cnn image-classification deep-learning machine-learning pytorch
Language:Jupyter Notebook 41
katiana22 / GDM-PCE
Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".
uncertainty-quantification polynomial-chaos-expansion surrogate-modelling manifold-learning machine-learning encoder-decoder-model
Language:Jupyter Notebook 35
ZJUFanLab / scRank
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
drug-response gene-network manifold-learning single-cell cell-type-prioritization
Language:R 30
LavieLuo / DRMEA
Pytorch code for “Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment ” (DRMEA) (AAAI 2020).
domain-adaptation manifold-learning aaai2020
Language:Python 29
RubixML / Credit
An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.
php machine-learning logistic-regression data-science classification credit-card rubix-ml dataset analytics t-sne manifold-learning pipeline tutorial example-project risk-assessment machine-learning-tutorial cross-validation monte-carlo-simulation php-ml php-machine-learning
Language:PHP 29
datafold-dev / datafold
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.
dynamic-mode-decomposition machine-learning manifold-learning dynamical-systems scientific-computing scikit-learn data-driven koopman-operator diffusion-map extended-dynamic-mode-decomposition time-series time-series-analysis
Language:Python 25
NLeSC / DiVE
An interactive 3D web viewer of up to million points on one screen that represent data. Provides interaction for viewing high-dimensional data that has been previously embedded in 3D or 2D. Based on graphosaurus.js and three.js. For a Linux release of a complete embedding+visualization pipeline please visit https://github.com/sonjageorgievska/Embed-Dive.
interactive-visualizations 3d-data embedded-data web-application manifold-learning non-linear-dimensionality-reduction high-dimensional-data
Language:HTML 25
TorchDR / TorchDR
TorchDR - PyTorch Dimensionality Reduction
dimensionality-reduction python manifold-learning optimal-transport affinity-matrix
Language:Python 21
stat-ml / GeoMLE
This repo contains code for GeoMLE intrinsic dimension estimation algorithm
intrinsic-dimension maximum-likelihood-estimation manifold-learning
Language:Jupyter Notebook 20
caokai1073 / Pamona
The software of Pamona, a partial manifold alignment algorithm.
single-cell-omics optimal-transport transfer-learning manifold-learning data-integration
Language:Jupyter Notebook 19
gd-vae / gd-vae
Geometric Dynamic Variational Autoencoders (GD-VAEs) for learning embedding maps for nonlinear dynamics into general latent spaces. This includes methods for standard latent spaces or manifold latent spaces with specified geometry and topology. The manifold latent spaces can be based on analytic expressions or general point cloud representations.
autoencoder-neural-network deep-learning dimension-reduction dynamical-systems geometric-algorithms geometric-deep-learning latent-spaces machine-learning manifold-learning neural-networks parameterized-systems point-cloud pytorch-implementation topological-data-analysis variational-autoencoder
Language:TeX 19
KevinMoonLab / GRAE
Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning
dimensionality-reduction autoencoder manifold-learning data-visualization unsupervised-learning deep-learning machine-learning
Language:Jupyter Notebook 19
LirongWu / GCML
Code for WACV 2022 paper "Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation"
clustering manifold-learning visualization
Language:Python 19
JAVI897 / Laplacian-Eigenmaps
Implemented Laplacian Eigenmaps
dimensionality-reduction manifold-learning spectral-embedding laplacian-eigenmaps
Language:Jupyter Notebook 18
LayneH / MRCNN
TensorFlow Implementation of Manifold Regularized Convolutional Neural Networks.
tensorflow transfer-learning convolutional-neural-networks manifold-learning fine-tune
Language:Python 17
techshot25 / Autoencoders
This will show how to make autoencoders using pytorch neural networks
autoencoder manifold-learning dimensionality-reduction pytorch-tutorials
Language:Jupyter Notebook 17