101 Open source projects that are alternatives of or similar to lfda

R package for Distance Metric Learning

Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (Neural Networks 2022 - in submission)

Recognize one of six human activities such as standing, sitting, and walking using a Softmax Classifier trained on mobile phone sensor data.

Parallel Barnes-Hut t-SNE implementation written in Rust.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Generalized Product Quantization Network For Semi-supervised Image Retrieval - CVPR 2020

A 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.

Learning Tree structures and Tree metrics

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition

ADENINE: A Data ExploratioN PipelINE

R wrappers to connect Python dimensional reduction tools and single cell data objects (Seurat, SingleCellExperiment, etc...)

🕝 Time-warped principal components analysis (twPCA)

Comparison of dimensionality reduction methods

A curated list of community detection research papers with implementations.

Uncertainty-aware principal component analysis.

tGPLVM: A Nonparametric, Generative Model for Manifold Learning with scRNA-seq experimental data

A fast and flexible framework for data reduction in R

Simple 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

Generalized Deep Metric Learning.

In this repository, You can find the files which implement dimensionality reduction on the hyperspectral image(Indian Pines) with classification.

Code for FOCAL Paper Published at ICLR 2021

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

A Tensorflow retrieval (space embedding) baseline. Metric learning baseline on CUB and Stanford Online Products.

awesome few shot / meta learning papers

This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.

Source code for the paper "Divide and Conquer the Embedding Space for Metric Learning", CVPR 2019

Awesome Few-shot learning

A repository of resources for understanding the concepts of machine learning/deep learning.

Using Kaggle Data and Real World Data for Data Science and prediction in Python, R, Excel, Power BI, and Tableau.

Streaming, Memory-Limited, r-truncated SVD Revisited!

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

Highly efficient PyTorch version of the Semi-hard Triplet loss ⚡️

Uniform Manifold Approximation and Projection

Ensemble topic modelling with pLSA

Online feature-extraction and classification algorithm that learns representations of input patterns.

A Python Library for Similarity-based Dimensionality Reduction

Workshop (6 hours): Clustering (Hdbscan, LCA, Hopach), dimension reduction (UMAP, GLRM), and anomaly detection (isolation forests).

Code for CVPR 2019 paper "Deep Metric Learning to Rank"

Context-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)

Accelerated deep learning R&D

Uniform Manifold Approximation and Projection (UMAP) implementation in Julia

Deep Metric and Hash Code Learning Network for Content Based Retrieval of Remote Sensing Images

A computational toolkit in R for the integration, exploration, and analysis of high-dimensional single-cell cytometry and imaging data.

Mathematical & 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.

Estimate dynamic high-order correlations in multivariate timeseries data

Code for Supervised Word Mover's Distance (SWMD)

Minimum-distortion embedding with PyTorch

Official PyTorch implementation of "Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning" (AAAI 2021)

Single-cell Hierarchical Poisson Factorization

Parametric UMAP embeddings for representation and semisupervised learning. From the paper "Parametric UMAP: learning embeddings with deep neural networks for representation and semi-supervised learning" (Sainburg, McInnes, Gentner, 2020).

TLDR is an unsupervised dimensionality reduction method that combines neighborhood embedding learning with the simplicity and effectiveness of recent self-supervised learning losses

Easy genetic ancestry predictions in Python

Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

(CVPR 2020) This repo contains code for "PADS: Policy-Adapted Sampling for Visual Similarity Learning", which proposes learnable triplet mining with Reinforcement Learning.

PyTorch code for BMVC 2018 paper: "Self-Paced Learning with Adaptive Visual Embeddings"

A comprehensive dimensional reduction framework to recover the latent topology from high-dimensional data.

Papers and Codes about Deep Metric Learning/Deep Embedding

This repository contains the code implementation used in the paper Temporally Coherent Embeddings for Self-Supervised Video Representation Learning (TCE).

Federated Principal Component Analysis Revisited!

Improved Deep Metric Learning with Multi-class N-pair Loss Objective