Build software better, together

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

tuanad121 / Python-WORLD

Star

audio python scale analysis vae pycharm pitch manifold-learning f0-analysis variational-autoencoder world-vocoder manifold-vocoder

Updated Dec 13, 2021
Python

dpeerlab / Palantir

Star

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 Dec 15, 2021
Jupyter Notebook

hwalsuklee / tensorflow-mnist-AAE

Star

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

naver / tldr

Star

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 Jan 10, 2022
Python

gdkrmr / dimRed

Star

A Framework for Dimensionality Reduction in R

visualization quality-control framework r high-dimensional-data dimensionality-reduction manifold-learning

Updated Mar 11, 2022
R

wildart / ManifoldLearning.jl

Star

A Julia package for manifold learning and nonlinear dimensionality reduction

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

Updated Mar 6, 2022
Julia

layer6ai-labs / GSS

Star

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

image-retrieval manifold-learning gcn neurips neurips-2019

Updated Aug 15, 2020
Python

zhanglabtools / DSMO.course

Star

Data Science and Matrix Optimization course

data-science course-materials matrix-factorization manifold-learning matrix-completion subspace-clustering manifold-alignment precision-matrix-estimation

Updated Sep 2, 2020

kisungyou / Rdimtools

Star

Dimension Reduction and Estimation Methods

r manifold-learning dimension-reduction subspace-learning dimension-estimation

Updated Feb 4, 2022
R

ecm200 / caltech_birds

Star

Open

ModuleNotFoundError: No module named 'pytorchcv.utils'

1

AlphaWu commented Aug 9, 2020

When I run 'script/train_pytorchcv_InceptionV4_caltech_birds.py', I get an error of 'ModuleNotFoundError: No module named 'pytorchcv.utils''.

My pytorchcv version is 0.058, and I install through pip.

Thanks.

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.

high-dimensional-data web-application manifold-learning interactive-visualizations 3d-data embedded-data non-linear-dimensionality-reduction

Updated Mar 12, 2018
HTML

RubixML / Credit

Sponsor

Star

An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.

php data-science machine-learning tutorial pipeline analytics taiwan dimensions cross-validation credit-card prediction labels dataset classification estimator logistic-regression monte-carlo-simulation t-sne example-project risk-assessment learners manifold-learning department php-ml credit-card-bill machine-learning-tutorial yeh rubix-ml php-machine-learning

Updated Apr 29, 2022
PHP

LavieLuo / DRMEA

Star

Pytorch code for “Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment ” (DRMEA) (AAAI 2020).

manifold-learning domain-adaptation aaai2020

Updated Aug 14, 2020
Python

LayneH / MRCNN

Star

TensorFlow Implementation of Manifold Regularized Convolutional Neural Networks.

tensorflow convolutional-neural-networks transfer-learning fine-tune manifold-learning

Updated May 14, 2017
Python

mdeff / dlaudio

Sponsor

Star

Master thesis: Structured Auto-Encoder with application to Music Genre Recognition (code)

deep-learning graphs music-information-retrieval sparse manifold-learning auto-encoders

Updated Apr 18, 2020
Jupyter Notebook

katiana22 / GDM-PCE

Star

Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models" arXiv:2107.09814v1.

machine-learning uncertainty-quantification manifold-learning encoder-decoder-model surrogate-modelling polynomial-chaos-expansion

Updated Dec 17, 2021
Jupyter Notebook

rmojgani / PhysicsAwareAE

Star

The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-uniform parameter/time-varying grid, such that the Kolmogorov n-width of the mapped data on the learned grid is minimized.