Topic: manifold-learning Goto Github
Some thing interesting about manifold-learning
Some thing interesting about manifold-learning
manifold-learning,A simple library for t-SNE animation and a zoom-in feature to apply t-SNE in that region
User: 0xshreyash
manifold-learning,The software of Pamona, a partial manifold alignment algorithm.
User: caokai1073
manifold-learning,Implementation of Low Distortion Local Eigenmaps and several variations of it
User: chiggum
Home Page: https://pyldle2.readthedocs.io/en/latest/
manifold-learning,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.
Organization: datafold-dev
Home Page: https://datafold-dev.gitlab.io/datafold/
manifold-learning,Systematically learn and evaluate manifolds from high-dimensional data
User: davisidarta
Home Page: https://topometry.readthedocs.io/en/latest/
manifold-learning,Single cell trajectory detection
Organization: dpeerlab
Home Page: https://palantir.readthedocs.io
manifold-learning,Introduction to Manifold Learning - Mathematical Theory and Applied Python Examples (Multidimensional Scaling, Isomap, Locally Linear Embedding, Spectral Embedding/Laplacian Eigenmaps)
User: drewwilimitis
Home Page: https://drewwilimitis.github.io/Manifold-Learning/
manifold-learning,A set of notebooks as a guide to the process of fine-grained image classification of birds species, using PyTorch based deep neural networks.
User: ecm200
manifold-learning,ManifoldEM Python suite
User: evanseitz
manifold-learning,We propose a density-based estimator for weighted geodesic distances suitable for data lying on a manifold of lower dimension than ambient space and sampled from a possibly nonuniform distribution
User: facusapienza21
Home Page: https://openreview.net/forum?id=BJfaMIJwG
manifold-learning,This is the code implementation for the GMML algorithm.
User: fenghaozhu
Home Page: https://ieeexplore.ieee.org/document/10623434
manifold-learning,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.
Organization: gd-vae
manifold-learning,A Framework for Dimensionality Reduction in R
User: gdkrmr
Home Page: https://www.guido-kraemer.com/software/dimred/
manifold-learning,A Matlab implementation of our previously published work in IEEE Trans. Big Data (TBD)
User: gitwr
manifold-learning,This is a matlab implementation of our article, named "SymNet: A Simple Symmetric Positive Definite Manifold Deep Learning Method for Image Set Classification", recently accepted by IEEE Transactions on Neural Networks and Learning Systems (TNNLS).
User: gitwr
manifold-learning,Matlab implementation of Diffusion Maps
User: gmishne
manifold-learning,Diffusion Net TensorFlow implementation
User: gmishne
manifold-learning,Statistical Machine Intelligence & Learning Engine
User: haifengl
Home Page: https://haifengl.github.io
manifold-learning,Tensorflow implementation of adversarial auto-encoder for MNIST
User: hwalsuklee
manifold-learning,Implemented Laplacian Eigenmaps
User: javi897
manifold-learning,Manifold-learning flows (ℳ-flows)
User: johannbrehmer
Home Page: https://arxiv.org/abs/2003.13913
manifold-learning,:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
User: justglowing
manifold-learning,Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".
User: katiana22
manifold-learning,Geometry Regularized Autoencoders (GRAE) for large-scale visualization and manifold learning
Organization: kevinmoonlab
manifold-learning,Dimension Reduction and Estimation Methods
User: kisungyou
Home Page: https://kisungyou.com/Rdimtools
manifold-learning,PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
Organization: krishnaswamylab
Home Page: http://phate.readthedocs.io
manifold-learning,Pytorch code for “Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment ” (DRMEA) (AAAI 2020).
User: lavieluo
manifold-learning,Code for the NeurIPS'19 paper "Guided Similarity Separation for Image Retrieval"
Organization: layer6ai-labs
manifold-learning,TensorFlow Implementation of Manifold Regularized Convolutional Neural Networks.
User: layneh
manifold-learning,Code for WACV 2022 paper "Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation"
User: lirongwu
manifold-learning,Master thesis: Structured Auto-Encoder with application to Music Genre Recognition (code)
User: mdeff
Home Page: https://infoscience.epfl.ch/record/218019
manifold-learning,Companion repository for the paper "Representation Learning via Manifold Flattening and Reconstruction"
User: michael-psenka
Home Page: https://www.michaelpsenka.io/papers/flatteningnetwork/
manifold-learning,TLDR is an unsupervised dimensionality reduction method that combines neighborhood embedding learning with the simplicity and effectiveness of recent self-supervised learning losses
Organization: naver
manifold-learning,Pytorch implementation of Hyperspherical Variational Auto-Encoders
User: nicola-decao
Home Page: http://arxiv.org/abs/1804.00891
manifold-learning,Tensorflow implementation of Hyperspherical Variational Auto-Encoders
User: nicola-decao
Home Page: http://arxiv.org/abs/1804.00891
manifold-learning,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.
Organization: nlesc
Home Page: https://NLeSC.github.io/DiVE/
manifold-learning,Discovering Conservation Laws using Optimal Transport and Manifold Learning
User: peterparity
Home Page: https://www.nature.com/articles/s41467-023-40325-7
manifold-learning,Python bindings to pressio
Organization: pressio
manifold-learning,PyTorch implementation of Bezier simplex fitting
Organization: rafcc
Home Page: https://pypi.org/project/pytorch-bsf/
manifold-learning,Code and reuslts accompanying the NeurIPS 2022 paper with the title SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
User: rkobler
manifold-learning,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.
User: rmojgani
manifold-learning,An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.
Organization: rubixml
Home Page: https://rubixml.com
manifold-learning,This repo contains code for GeoMLE intrinsic dimension estimation algorithm
Organization: stat-ml
manifold-learning,This will show how to make autoencoders using pytorch neural networks
User: techshot25
manifold-learning,CellRank: dynamics from multi-view single-cell data
Organization: theislab
Home Page: https://cellrank.org
manifold-learning,TorchDR - PyTorch Dimensionality Reduction
Organization: torchdr
Home Page: https://torchdr.github.io/dev/
manifold-learning,
User: tuanad121
manifold-learning,A Julia package for manifold learning and nonlinear dimensionality reduction
User: wildart
manifold-learning,Data Science and Matrix Optimization course
Organization: zhanglabtools
manifold-learning,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
User: zjufanlab
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