Python Contrastive-Clustering Resources

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering Jang Hyun Cho1, Utkarsh Mall2, Kavita Bala2, Bharath Harihar

How to Reproduce our Results This repository contains PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Represen

Neighborhood Contrastive Learning for Novel Class Discovery This repository contains the official implementation of our paper: Neighborhood Contrastiv

Supporting Clustering with Contrastive Learning SCCL (NAACL 2021) Dejiao Zhang, Feng Nan, Xiaokai Wei, Shangwen Li, Henghui Zhu, Kathleen McKeown, Ram

This is a release of our VIMPAC paper to illustrate the implementations. The pretrained checkpoints and scripts will be soon open-sourced in HuggingFace transformers.

Deep Conditional Gaussian Mixture Model for Constrained Clustering. This repository holds the code for the paper Deep Conditional Gaussian Mixture Mod

Segmentation and Identification of Vertebrae in CT Scans using CNN, k-means Clustering and k-NN If you use this code for your research, please cite ou

Graph Contrastive Learning Automated PyTorch implementation for Graph Contrastive Learning Automated [talk] [poster] [appendix] Yuning You, Tianlong C

Self-Damaging Contrastive Learning Introduction The recent breakthrough achieved by contrastive learning accelerates the pace for deploying unsupervis

SPICE: Semantic Pseudo-labeling for Image Clustering By Chuang Niu and Ge Wang This is a Pytorch implementation of the paper. (In updating) SOTA on 5

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations This repo contains the Pytorch implementation of our paper: Revisit

This repository is the official PyTorch implementation of SAINT. Find the paper on arxiv SAINT: Improved Neural Networks for Tabular Data via Row Atte

ERICA Source code and dataset for ACL2021 paper: "ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive L

SimCLS Code for our paper: "SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization", ACL 2021 1. How to Install Requirements

ConSERT Code for our ACL 2021 paper - ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer Requirements torch==1.6.0

ConSERT Code for our ACL 2021 paper - ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer Requirements torch==1.6.0

PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

Video Person Clustering Repo for the Video Person Clustering dataset, and code for the associated paper. This reporsitory contains the Video Person Cl

Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts The rapid progress in 3D scene understanding has come with growing dem

SelfReg PyTorch official implementation of Self-supervised Contrastive Regularization for Domain Generalization (SelfReg, https://arxiv.org/abs/2104.0

GCA Source code for Graph Contrastive Learning with Adaptive Augmentation (WWW 2021) For example, to run GCA-Degree under WikiCS, execute: python trai

CURL Rainbow Status: Archive (code is provided as-is, no updates expected) This is an implementation of CURL: Contrastive Unsupervised Representations

Self-Supervised Music Analysis Self-Supervised Contrastive Learning of Music Spectrograms Dataset Songs on the Billboard Year End Hot 100 were collect

30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms

UIS-RNN Overview This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm. UIS-RNN solves the problem of s

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Unsupervised Contrastive Learning of Sound Event Representations This repository contains the code for the following paper. If you use this code or pa

CLAP Contrastive Language-Audio Pretraining In due time this repo will be full of lovely things, I hope. Feel free to check out the Issues if you're i

arXiv Dual Contrastive Learning Adversarial Generative Networks (DCLGAN) We provide our PyTorch implementation of DCLGAN, which is a simple yet powerf

SimCSE: Simple Contrastive Learning of Sentence Embeddings This repository contains the code and pre-trained models for our paper SimCSE: Simple Contr

SpikeX is a collection of pipes ready to be plugged in a spaCy pipeline. It aims to help in building knowledge extraction tools with almost-zero effort.

Contrastive Tension State of the art Semantic Sentence Embeddings Published Paper · Huggingface Models · Report Bug Overview This is the official code

ReCo - Regional Contrast This repository contains the source code of ReCo and baselines from the paper, Bootstrapping Semantic Segmentation with Regio

CLASP - Contrastive Language-Aminoacid Sequence Pretraining Repository for creating models pretrained on language and aminoacid sequences similar to C

STAR-FC This code is the implementation for the CVPR 2021 paper "Structure-Aware Face Clustering on a Large-Scale Graph with 10^7 Nodes" 🌟 🌟 . 🎓 Re

Completer: Incomplete Multi-view Clustering via Contrastive Prediction This repo contains the code and data of the following paper accepted by CVPR 20

An open-source library of algorithms to analyse time series in GPU and CPU.

Improving Unsupervised Image Clustering With Robust Learning This repo is the PyTorch codes for "Improving Unsupervised Image Clustering With Robust L

FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding (CVPR 2021) This repo contains the implementation of our state-of-the-art fewshot ob

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

VitaminC This repository contains the dataset and models for the NAACL 2021 paper: Get Your Vitamin C! Robust Fact Verification with Contrastive Evide

CoMatch: Semi-supervised Learning with Contrastive Graph Regularization (Salesforce Research) This is a PyTorch implementation of the CoMatch paper [B

gHHC Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, D

Training GANs with Stronger Augmentations via Contrastive Discriminator (ICLR 2021) This repository contains the code for reproducing the paper: Train

Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning By Zhenda Xie*, Yutong Lin*, Zheng Zhang, Yue Ca

Contrastive Explanation (Foil Trees) Contrastive and counterfactual explanations for machine learning (ML) Marcel Robeer (2018-2020), TNO/Utrecht Univ

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

Dense Contrastive Learning for Self-Supervised Visual Pre-Training This project hosts the code for implementing the DenseCL algorithm for se

Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program

Unsupervised Semantic Segmentation by Contrasting Object Mask Proposals This repo contains the Pytorch implementation of our paper: Unsupervised Seman

SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algorithms that do the job in the least jargon possible and examples to guide you through every step of the way.

Official code to reproduce the results and data presented in the paper Contrastive Learning Inverts the Data Generating Process.

Text preprocessing, representation and visualization from zero to hero. From zero to hero • Installation • Getting Started • Examples • API • FAQ • Co

Dedupe Python Library dedupe is a python library that uses machine learning to perform fuzzy matching, deduplication and entity resolution quickly on

Exploring Cross-Image Pixel Contrast for Semantic Segmentation Exploring Cross-Image Pixel Contrast for Semantic Segmentation, Wenguan Wang, Tianfei Z

Text preprocessing, representation and visualization from zero to hero. From zero to hero • Installation • Getting Started • Examples • API • FAQ • Co

Dedupe Python Library dedupe is a python library that uses machine learning to perform fuzzy matching, deduplication and entity resolution quickly on

Contrastive Clustering (CC) This is the code for the paper "Contrastive Clustering" (AAAI 2021) Dependency python=3.7 pytorch=1.6.0 torchvision=0.8

SupCon-Framework The repo is an implementation of Supervised Contrastive Learning. It's based on another implementation, but with several differencies

NeMo: Neural Mesh Models of Contrastive Features for Robust 3D Pose Estimation [ICLR-2021] Release Notes The offical PyTorch implementation of NeMo, p

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

HDBSCAN Now a part of scikit-learn-contrib HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over va

Dedupe Python Library dedupe is a python library that uses machine learning to perform fuzzy matching, deduplication and entity resolution quickly on

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext