UmapUniform Manifold Approximation and Projection
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UMAP.jlUniform Manifold Approximation and Projection (UMAP) implementation in Julia
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M-NMFAn implementation of "Community Preserving Network Embedding" (AAAI 2017)
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dbMAPA fast, accurate, and modularized dimensionality reduction approach based on diffusion harmonics and graph layouts. Escalates to millions of samples on a personal laptop. Adds high-dimensional big data intrinsic structure to your clustering and data visualization workflow.
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ReductionWrappersR wrappers to connect Python dimensional reduction tools and single cell data objects (Seurat, SingleCellExperiment, etc...)
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Data-ScienceUsing Kaggle Data and Real World Data for Data Science and prediction in Python, R, Excel, Power BI, and Tableau.
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FUSIONPyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"
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Awesome Single CellCommunity-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
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Competitive-Feature-LearningOnline feature-extraction and classification algorithm that learns representations of input patterns.
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federated pcaFederated Principal Component Analysis Revisited!
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image embeddingsUsing efficientnet to provide embeddings for retrieval
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NIDS-Intrusion-DetectionSimple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN
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DESOM🌐 Deep Embedded Self-Organizing Map: Joint Representation Learning and Self-Organization
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partitionA fast and flexible framework for data reduction in R
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PLBARTOfficial code of our work, Unified Pre-training for Program Understanding and Generation [NAACL 2021].
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REGALRepresentation learning-based graph alignment based on implicit matrix factorization and structural embeddings
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mathematics-statistics-for-data-scienceMathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.
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tGPLVMtGPLVM: A Nonparametric, Generative Model for Manifold Learning with scRNA-seq experimental data
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GLOM-TensorFlowAn attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data
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dmlR package for Distance Metric Learning
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VQ-APCVector Quantized Autoregressive Predictive Coding (VQ-APC)
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SpectreA computational toolkit in R for the integration, exploration, and analysis of high-dimensional single-cell cytometry and imaging data.
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timecorrEstimate dynamic high-order correlations in multivariate timeseries data
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Revisiting-Contrastive-SSLRevisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]
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pymdeMinimum-distortion embedding with PyTorch
Stars: ✭ 420 (+218.18%)
twpca🕝 Time-warped principal components analysis (twPCA)
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sefA Python Library for Similarity-based Dimensionality Reduction
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GraphMixCode for reproducing results in GraphMix paper
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COCO-LM[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
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Learning-From-RulesImplementation of experiments in paper "Learning from Rules Generalizing Labeled Exemplars" to appear in ICLR2020 (https://openreview.net/forum?id=SkeuexBtDr)
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Machine Learning With PythonPractice and tutorial-style notebooks covering wide variety of machine learning techniques
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PCC-pytorchA pytorch implementation of the paper "Prediction, Consistency, Curvature: Representation Learning for Locally-Linear Control"
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HARRecognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.
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MTL-AQAWhat and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment [CVPR 2019]
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anatomeἈνατομή is a PyTorch library to analyze representation of neural networks
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scHPFSingle-cell Hierarchical Poisson Factorization
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object-aware-contrastiveObject-aware Contrastive Learning for Debiased Scene Representation (NeurIPS 2021)
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tldrTLDR is an unsupervised dimensionality reduction method that combines neighborhood embedding learning with the simplicity and effectiveness of recent self-supervised learning losses
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mosesStreaming, Memory-Limited, r-truncated SVD Revisited!
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PC3-pytorchPredictive Coding for Locally-Linear Control (ICML-2020)
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bhtsneParallel Barnes-Hut t-SNE implementation written in Rust.
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causal-mlMust-read papers and resources related to causal inference and machine (deep) learning
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ezancestryEasy genetic ancestry predictions in Python
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adenineADENINE: A Data ExploratioN PipelINE
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reprieveA library for evaluating representations.
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walkletsA lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).
Stars: ✭ 94 (-28.79%)
50-days-of-Statistics-for-Data-ScienceThis repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.
Stars: ✭ 19 (-85.61%)
Machine LearningA repository of resources for understanding the concepts of machine learning/deep learning.
Stars: ✭ 29 (-78.03%)
TCEThis repository contains the code implementation used in the paper Temporally Coherent Embeddings for Self-Supervised Video Representation Learning (TCE).
Stars: ✭ 51 (-61.36%)
scarfToolkit 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.
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uapcaUncertainty-aware principal component analysis.
Stars: ✭ 16 (-87.88%)
DRComparisonComparison of dimensionality reduction methods
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pgdlWinning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning
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