Python Supervised-clustering Resources

Self-Supervised Bug Detection and Repair This is the reference code to replicate the research in Self-Supervised Bug Detection and Repair in NeurIPS 2

ExCon: Explanation-driven Supervised Contrastive Learning Contributors of this repo: Zhibo Zhang ([email protected]) Jongseong Jang (j.jang@lg

Semi-supervised Implicit Scene Completion from Sparse LiDAR Paper Created by Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou and YA-QIN ZH

Repository for the paper "Graph Auto-Encoders for Financial Clustering" Requirements Python 3.6 torch torch_geometric Instructions This is a simple c

Self Supervised clusterer Combined IIC, and Moco architectures, with some SimCLR notions, to get state of the art unsupervised clustering while retain

Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning. This repo contains the PyTorch code and implementation for the paper E

Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning. Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive

Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks This repository contains the official code for the

Steps to run = Download the cora dataset from this link : https://linqs.soe.ucsc.edu/data unzip the files in the folder input/cora cd code python eda

BanditPAM: Almost Linear-Time k-Medoids Clustering This repo contains a high-performance implementation of BanditPAM from BanditPAM: Almost Linear-Tim

Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.

Sequence clustering and database creation using mmseqs, from local fasta files

BANA This is the implementation of the paper "Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation". For more inf

Learning Pixel-level Semantic Affinity with Image-level Supervision This code is deprecated. Please see https://github.com/jiwoon-ahn/irn instead. Int

SSC-GAN_repo Pytorch implementation for 'Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation'.PDF SSC-GAN:Sem

Bootstrap Your Own Latent (BYOL), in Pytorch Practical implementation of an astoundingly simple method for self-supervised learning that achieves a ne

Semi-supervised Implicit Scene Completion from Sparse LiDAR Paper Created by Pengfei Li, Yongliang Shi, Tianyu Liu, Hao Zhao, Guyue Zhou and YA-QIN ZH

Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur

ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).

TeST: Temporal-Stable Thresholding for Semi-supervised Learning TeST Illustration Semi-supervised learning (SSL) offers an effective method for large-

Semi-Supervised Learning for Fine-Grained Classification This repo contains the code of: A Realistic Evaluation of Semi-Supervised Learning for Fine-G

Self-Supervised Pre-Training for Transformer-Based Person Re-Identification [pdf] The official repository for Self-Supervised Pre-Training for Transfo

PSSL Source code of CIKM2021 Long Paper "PSSL: Self-supervised Learning for Personalized Search with Contrastive Sampling". It consists of the pre-tra

DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning Pytorch Implementation for DisCo: Remedy Self-supervi

ICCVW21-TradiCV-Survey-of-LiDAR-Cluster Motivation In contrast to popular end-to-end deep learning LiDAR panoptic segmentation solutions, we propose a

SE(3)-eSCOPE video | paper | website Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation Xiaolong Li, Yijia Weng,

Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati

Self-Supervised Document Similarity Ranking (SDR) via Contextualized Language Models and Hierarchical Inference This repo is the implementation for SD

Self Supervised Learning with Fastai Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks. Install pip install self-

cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear

MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data. We demonstrate its use

DABS: A Domain Agnostic Benchmark for Self-Supervised Learning This repository contains the code for DABS, a benchmark for domain-agnostic self-superv

Tutela: an Ethereum and Tornado Cash Anonymity Tool The repo contains open-source code for Tutela, an anonymity tool for Ethereum and Tornado Cash use

WSDEC This is the official repo for our NeurIPS paper Weakly Supervised Dense Event Captioning in Videos. Description Repo directories ./: global conf

Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv

Make Complex Heatmaps Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. H

An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu

Faiss Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any

Infomap Infomap is a network clustering algorithm based on the Map equation. For detailed documentation, see mapequation.org/infomap. For a list of re

Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.

Self-Supervised Monocular 3D Face Reconstruction by Occlusion-Aware Multi-view Geometry Consistency(ECCV 2020) This is an official python implementati

DSM The source code for paper Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion Project Website; Datasets li

Barlow-Twins-TF This repository implements Barlow Twins (Barlow Twins: Self-Supervised Learning via Redundancy Reduction) in TensorFlow and demonstrat

MSc-Thesis Module: Masters Research Thesis Language: Python Grade: 75 Title: An investigation of supervised classification of therapeutic process from

Microscopium Unsupervised clustering and dataset exploration for high content screens. See microscopium in action Public dataset BBBC021 from the Broa

Unsupervised-Machine-Learning Flat Clustering K-Means clusternig example with Python and Scikit-learn Flat clustering Clustering algorithms group a se

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

sm_content_clustering A Python module for clustering creators of social media content into networks. Currently supports identifying potential networks

Introduction This is a repository of our model for weakly-supervised video dense anticipation. More results on GTEA, Epic-Kitchens etc. will come soon

English | 简体中文 Latest News 2021.10.25 Paper "Docking-based Virtual Screening with Multi-Task Learning" is accepted by BIBM 2021. 2021.07.29 PaddleHeli

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks This is a Pytorch-Lightning implementation of the paper "Self-s

MAE for Self-supervised ViT Introduction This is an unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners for self-sup

Self Organising Map for Clustering of Atomistic Samples - V2 Description Self Organising Map (also known as Kohonen Network) implemented in Python for

What's New Below we share, in reverse chronological order, the updates and new releases in VISSL. All VISSL releases are available here. [Oct 2021]: V

HDBSCAN HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with Noise. Performs DBSCAN over varying epsilon values and integrates

pyclustering is a Python, C++ data mining library (clustering algorithm, oscillatory networks, neural networks). The library provides Python and C++ implementations (C++ pyclustering library) of each algorithm or model. C++ pyclustering library is a part of pyclustering and supported for Linux, Windows and MacOS operating systems.

FCPS Fundamental Clustering Problems Suite The package provides over sixty state-of-the-art clustering algorithms for unsupervised machine learning pu

Buckshot++: An Outlier-Resistant and Scalable Clustering Algorithm. (Inspired by the Buckshot Algorithm.) Here, we introduce a new algorithm, which we

tree-SNE t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology. Building on recent advances in s

MiniSom Self Organizing Maps MiniSom is a minimalistic and Numpy based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial N

Description Implements (high-dimenstional) clustering algorithm described in https://arxiv.org/pdf/1804.02624.pdf Dependencies python3 pytorch (=0.4)

Hyperbolic Hierarchical Clustering (HypHC) This code is the official PyTorch implementation of the NeurIPS 2020 paper: From Trees to Continuous Embedd

CG3 This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning]. R

JBHI-Pytorch This repository contains a reference implementation of the algorithms described in our paper "Self-supervised Multi-modal Hybrid Fusion N

SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks

self-supervised-landmarks Repository for self-supervised landmark discovery Requirements pytorch pynrrd (for 3d images) Usage The use of this models i

Spectral-spatial contrastive clustering (SSCC) Yaoming Cai, Yan Liu, Zijia Zhang, Zhihua Cai, and Xiaobo Liu, Large-scale Hyperspectral Image Clusteri

G2S This is the official code for ICRA 2021 Paper: Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth Estimation by Hemang

SCCKTIM Weakly Supervised 3D Object Detection from Point Cloud with Only Image-Level Annotation Our code will be available soon. The class knowledge t

IMDB film review sentiment classification based on BERT's supervised learning model. On the other hand, the model can be extended to other natural language multi-classification tasks.

Music Classification: Beyond Supervised Learning, Towards Real-world Applications

Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style [NeurIPS 2021] Official code to reproduce the results and data p

S-multi-SNE Supervised multi-SNE (S-multi-SNE): Multi-view visualisation and classification A repository containing the code to reproduce the findings

Introduction Official implementation of "Membership Inference Attacks Against Self-supervised Speech Models". In this work, we demonstrate that existi

Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On [Project website] [Dataset] [Video] Abstract We propose a new g

Just Ask: Learning to Answer Questions from Millions of Narrated Videos Webpage • Demo • Paper This repository provides the code for our paper, includ

Introduction Datasets and source code for our paper Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach Datasets: WebFG-496

RTFM This repo contains the Pytorch implementation of our paper: Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Lear

ADDS-DepthNet This is the official implementation of the paper Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation I

DARS Code release for the paper "Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation", ICCV 2021

MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving Code will be available soon. Motivation Architecture

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

RSC-Net: 3D Human Pose, Shape and Texture from Low-Resolution Images and Videos Implementation for "3D Human Pose, Shape and Texture from Low-Resoluti

cLoops2: full stack analysis tool for chromatin interactions Introduction cLoops2 is an extension of our previous work, cLoops. From loop-calling base

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval Pytorch implementation of SPQ Accepted to ICCV 2021 - paper Young Kyun Jang

Fair-SSL Source Code for ICSE 2022 Paper - Can We Achieve Fairness Using Semi-Supervised Learning? Ethical bias in machine learning models has become

FastCover: A Self-Supervised Learning Framework for Multi-Hop Influence Maximization in Social Networks by Anonymous.

Contrastive Self-Supervised Learning on CIFAR-10 Paper "Towards the Generalization of Contrastive Self-Supervised Learning", Weiran Huang, Mingyang Yi

Lidar-Segementation An implementation on "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance" from

deeptime Releases: Installation via conda recommended. conda install -c conda-forge deeptime pip install deeptime Documentation: deeptime-ml.github.io

Pseudo-mask Matters in Weakly-supervised Semantic Segmentation By Yi Li, Zhanghui Kuang, Liyang Liu, Yimin Chen, Wayne Zhang SenseTime, Tsinghua Unive

Lossy Compression for Lossless Prediction Using: Training: This repostiory contains our implementation of the paper: Lossy Compression for Lossless Pr

Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering

Intermdiate layer matters - SSL The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper. Downl

Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The offical PyTorch implementation of Neural View Sy

TransMaS This repository is the official pytorch implementation of the following paper: NIPS2021 Mixed Supervised Object Detection by TransferringMask

IP-IRM [NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature". Codes will be relea

[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

K Means Algorithm What is K Means This algorithm is an iterative algorithm that partitions the dataset according to their features into K number of pr

We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.