A flexible and efficient С++ template library for dimension reduction
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Jun 17, 2024 - C++
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dimension-reduction
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numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法
machine-learning clustering numpy svm regression python3 classification gbdt ensemble decision-tree dimension-reduction boosting lr
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Dec 6, 2019 - Python
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
visualization gui shiny clustering gene-expression feature-extraction transcriptomics single-cell hacktoberfest dimension-reduction human-cell-atlas
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Dec 10, 2024 - R
A fast xgboost feature selection algorithm
data-science machine-learning algorithm machine-learning-algorithms feature-selection datascience xgboost machinelearning boruta dimension-reduction datascientist xgboost-algorithm
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Apr 1, 2021 - Python
Deep learning meets molecular dynamics.
python markov-model machine-learning deep-learning time-series tensorflow computational-biology pytorch computational-chemistry autoencoder data-analysis dimension-reduction
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May 3, 2019 - Jupyter Notebook
Randomized Dimension Reduction Library
python pca svd principal-component-analysis dimension-reduction lu-decomposition singular-value-decomposition randomized-algorithm nonnegative-matrix-factorization matrix-approximation dynamic-mode-decomposition
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Apr 17, 2021 - Jupyter Notebook
Randomized Matrix Decompositions using R
cran pca svd principal-component-analysis dimension-reduction singular-value-decomposition randomized-algorithm matrix-approximation probabilistic-algorithms
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Apr 13, 2021 - R
Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.
bioinformatics big-data genomics clustering scrna-seq graph-analytics memory-efficient tsne differential-expression umap dimension-reduction single-cell-genomics single-cell-rna-seq scalable-data-analysis single-cell-atac-seq multiomics cite-seq pseudotime scatac-seq gene-modules
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Oct 23, 2024 - Python
A header-only C++ library for sketching in randomized linear algebra
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Oct 24, 2024 - C++
Fast k-Nearest Neighbors Classifier for Large Datasets
kaggle feature-extraction rstats nearest-neighbors feature-engineering knn decision-boundaries shrinkage-estimator dimension-reduction
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Sep 17, 2017 - R
Sparse Principal Component Analysis (SPCA) using Variable Projection
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Apr 7, 2018 - R
Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
regression partial-differential-equations materials-science fluid-dynamics dimension-reduction latent-spaces deeponet neural-operators
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Jul 25, 2024 - Python
Dimension Reduction and Estimation Methods
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Dec 15, 2022 - R
A fast, scalable and light-weight C++ Fréchet and DTW distance library, exposed to python and focused on clustering of polygonal curves.
python algorithm time-series clustering trajectory-analysis dynamic-time-warping dimension-reduction trajectory distance-calculation frechet-distance sequential-data trajectory-clustering fr-chet-distance frechet polygonal-chain continuous-frechet-distance dimensional-polygonal-curves nearest-centers sampling-algorithms polygonal-curves
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Aug 29, 2023 - C++
R wrappers to connect Python dimensional reduction tools and single cell data objects (Seurat, SingleCellExperiment, etc...)
python wrapper bioinformatics dimensionality-reduction tsne forceatlas2 umap dimension-reduction force-directed-graphs wrappers seurat singlecellexperiment singlecellexperiment-objects paga phate opentsne pacmap dimensional-reduction
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Dec 6, 2024 - R
Dimension reduced surrogate construction for parametric PDE maps
deep-learning neural-networks dimensionality-reduction reduced-basis dimension-reduction proper-orthogonal-decomposition surrogate-models reduced-order-surrogate-model active-subspace karhunen-loeve reduced-order-modeling parametric-pde parametric-pdes
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Dec 11, 2024 - Python
Reconstruction and Compression of Color Images Using Principal Component Analysis (PCA) Algorithm
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Jun 3, 2020 - Python
Statistical quality evaluation of dimensionality reduction algorithms
high-dimensional-data dimensionality-reduction dimension-reduction scrna-seq-analysis high-dimension-visualization
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Aug 21, 2023 - Jupyter Notebook
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.
machine-learning deep-learning point-cloud neural-networks dynamical-systems manifold-learning dimension-reduction geometric-algorithms topological-data-analysis variational-autoencoder parameterized-systems geometric-deep-learning pytorch-implementation autoencoder-neural-network latent-spaces
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Aug 30, 2023 - TeX
manage ordinations and render biplots in a tidyverse workflow
tidyverse data-visualization dimension-reduction ordination biplot multivariate-analysis multivariate-statistics tidymodels geometric-data-analysis grammar-of-graphics log-ratio-analysis
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Dec 9, 2024 - R
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