1311 Repositories
Python graph-classification Libraries
Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible
IMBENS: Class-imbalanced Ensemble Learning in Python Language: English | Chinese/中文 Links: Documentation | Gallery | PyPI | Changelog | Source | Downl
PyTorch Implementation of SSTNs for hyperspectral image classifications from the IEEE T-GRS paper "Spectral-Spatial Transformer Network for Hyperspectral Image Classification: A FAS Framework."
PyTorch Implementation of SSTN for Hyperspectral Image Classification Paper links: SSTN published on IEEE T-GRS. Also, you can directly find the imple
TransPrompt - Towards an Automatic Transferable Prompting Framework for Few-shot Text Classification
TransPrompt This code is implement for our EMNLP 2021's paper 《TransPrompt:Towards an Automatic Transferable Prompting Framework for Few-shot Text Cla
MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification
MixText This repo contains codes for the following paper: Jiaao Chen, Zichao Yang, Diyi Yang: MixText: Linguistically-Informed Interpolation of Hidden
Class-Attentive Diffusion Network for Semi-Supervised Classification [AAAI'21] (official implementation)
Class-Attentive Diffusion Network for Semi-Supervised Classification Official Implementation of AAAI 2021 paper Class-Attentive Diffusion Network for
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning Source code for AISTATS 2019 paper: Confidence-based Graph Convolutional Ne
Training neural models with structured signals.
Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured
Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Learning with Nonignorable Nonresponses‘
Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear
A Flexible Generative Framework for Graph-based Semi-supervised Learning (NeurIPS 2019)
G3NN This repo provides a pytorch implementation for the 4 instantiations of the flexible generative framework as described in the following paper: A
Meta Learning for Semi-Supervised Few-Shot Classification
few-shot-ssl-public Code for paper Meta-Learning for Semi-Supervised Few-Shot Classification. [arxiv] Dependencies cv2 numpy pandas python 2.7 / 3.5+
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
CCCL: Contrastive Cascade Graph Learning.
CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr
GitHub Activity Generator - A script that helps you instantly generate a beautiful GitHub Contributions Graph for the last year.
GitHub Activity Generator A script that helps you instantly generate a beautiful GitHub Contributions Graph for the last year. Before 😐 😶 😒 After ?
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N
PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE).
GRACE The official PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE). For a thorough resource collection of self-superv
Graph Representation Learning via Graphical Mutual Information Maximization
GMI (Graphical Mutual Information) Graph Representation Learning via Graphical Mutual Information Maximization (Peng Z, Huang W, Luo M, et al., WWW 20
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"
SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th
Pretraining on Dynamic Graph Neural Networks
Pretraining on Dynamic Graph Neural Networks Our article is PT-DGNN and the code is modified based on GPT-GNN Requirements python 3.6 Ubuntu 18.04.5 L
An implementation of Deep Graph Infomax (DGI) in PyTorch
DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom
Unsupervised Attributed Multiplex Network Embedding (AAAI 2020)
Unsupervised Attributed Multiplex Network Embedding (DMGI) Overview Nodes in a multiplex network are connected by multiple types of relations. However
Heterogeneous Deep Graph Infomax
Heterogeneous-Deep-Graph-Infomax Parameter Setting: HDGI-A: Node-level dimension: 16 Attention head: 4 Semantic-level attention vector: 8 learning rat
Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"
Subg-Con Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning (Jiao et al., ICDM 2020): https://arxiv.org/abs/2009.10273 Over
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu
This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.
This project aim to create multi-label classification annotation tool to boost annotation speed and make it more easier.
A Python server and client app that tracks player session times and server status
MC Outpost A Python server and client application that tracks player session times and server status About MC Outpost provides a session graph and ser
Scientific measurement library for instruments, experiments, and live-plotting
PyMeasure scientific package PyMeasure makes scientific measurements easy to set up and run. The package contains a repository of instrument classes a
The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution
Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe
Source code of the "Graph-Bert: Only Attention is Needed for Learning Graph Representations" paper
Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.
Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training
PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
Pre-training of Graph Augmented Transformers for Medication Recommendation
G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be
Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa
Deeper insights into graph convolutional networks for semi-supervised learning
deeper_insights_into_GCNs Deeper insights into graph convolutional networks for semi-supervised learning References data and utils.py come from Implem
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels"
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels" Please refer to htt
code for "Self-supervised edge features for improved Graph Neural Network training", arxivlink
Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages
DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program
Code for hyperboloid embeddings for knowledge graph entities
Implementation for the papers: Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs, Nurendra Choudhary, Nikhil Rao,
Official code for the paper "Self-Supervised Prototypical Transfer Learning for Few-Shot Classification"
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification This repository contains the reference source code and pre-trained models (
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
Learning to Classify Images without Labels This repo contains the Pytorch implementation of our paper: SCAN: Learning to Classify Images without Label
Pytorch implementation of the AAAI 2022 paper "Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification"
[AAAI22] Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification We point out the overlooked unbiasedness in long-tailed clas
nlpcommon is a python Open Source Toolkit for text classification.
nlpcommon nlpcommon, Python Text Tool. Guide Feature Install Usage Dataset Contact Cite Reference Feature nlpcommon is a python Open Source
The code for SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network.
SAG-DTA The code is the implementation for the paper 'SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network'. Requirements py
Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition (AGRA, ACM 2020, Oral)
Cross Domain Facial Expression Recognition Benchmark Implementation of papers: Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchm
Retrieve annotated intron sequences and classify them as minor (U12-type) or major (U2-type)
(intron I nterrogator and C lassifier) intronIC is a program that can be used to classify intron sequences as minor (U12-type) or major (U2-type), usi
Medical-Image-Triage-and-Classification-System-Based-on-COVID-19-CT-and-X-ray-Scan-Dataset
Medical-Image-Triage-and-Classification-System-Based-on-COVID-19-CT-and-X-ray-Sc
LazyText is inspired b the idea of lazypredict, a library which helps build a lot of basic models without much code.
LazyText is inspired b the idea of lazypredict, a library which helps build a lot of basic models without much code. LazyText is for text what lazypredict is for numeric data.
The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding"
AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:
Rule based classification A hotel s customers dataset
Rule-based-classification-A-hotel-s-customers-dataset- Aim: Categorize new customers by segment and predict how much revenue they can generate This re
Build a medical knowledge graph based on Unified Language Medical System (UMLS)
UMLS-Graph Build a medical knowledge graph based on Unified Language Medical System (UMLS) Requisite Install MySQL Server 5.6 and import UMLS data int
MS Graph API authentication example with Fast API
MS Graph API authentication example with Fast API What it is & does This is a simple python service/webapp, using FastAPI with server side rendering,
LynxKite: a complete graph data science platform for very large graphs and other datasets.
LynxKite is a complete graph data science platform for very large graphs and other datasets. It seamlessly combines the benefits of a friendly graphical interface and a powerful Python API.
AAAI 2022 paper - Unifying Model Explainability and Robustness for Joint Text Classification and Rationale Extraction
AT-BMC Unifying Model Explainability and Robustness for Joint Text Classification and Rationale Extraction (AAAI 2022) Paper Prerequisites Install pac
Spaghetti: an open-source Python library for the analysis of network-based spatial data
pysal/spaghetti SPAtial GrapHs: nETworks, Topology, & Inference Spaghetti is an open-source Python library for the analysis of network-based spatial d
A visualization tool to show a TensorFlow's graph like TensorBoard
tfgraphviz tfgraphviz is a module to visualize a TensorFlow's data flow graph like TensorBoard using Graphviz. tfgraphviz enables to provide a visuali
An End-to-End Machine Learning Library to Optimize AUC (AUROC, AUPRC).
Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a
Build an Amazon SageMaker Pipeline to Transform Raw Texts to A Knowledge Graph
Build an Amazon SageMaker Pipeline to Transform Raw Texts to A Knowledge Graph This repository provides a pipeline to create a knowledge graph from ra
🐍PyNode Next allows you to easily create beautiful graph visualisations and animations
PyNode Next A complete rewrite of PyNode for the modern era. Up to five times faster than the original PyNode. PyNode Next allows you to easily create
Example Code Notebooks for Data Visualization in Python
This repository contains sample code scripts for creating awesome data visualizations from scratch using different python libraries (such as matplotli
Quick insights from Zoom meeting transcripts using Graph + NLP
Transcript Analysis - Graph + NLP This program extracts insights from Zoom Meeting Transcripts (.vtt) using TigerGraph and NLTK. In order to run this
Random Directed Acyclic Graph Generator
DAG_Generator Random Directed Acyclic Graph Generator verison1.0 简介 工作流通常由DAG(有向无环图)来定义,其中每个计算任务$T_i$由一个顶点(node,task,vertex)表示。同时,任务之间的每个数据或控制依赖性由一条加权
Code for "Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals," CoRL 2021.
Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversals This repository contains code for "Multimodal trajectory prediction conditioned
Official Pytorch implementation of the paper: "Locally Shifted Attention With Early Global Integration"
Locally-Shifted-Attention-With-Early-Global-Integration Pretrained models You can download all the models from here. Training Imagenet python -m torch
Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"
Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching This repository is an official implementation of
NeoInterface - Neo4j made easy for Python programmers!
Neointerface - Neo4j made easy for Python programmers! A Python interface to use the Neo4j graph database, and simplify its use. class NeoInterface: C
Official code for the publication "HyFactor: Hydrogen-count labelled graph-based defactorization Autoencoder".
HyFactor Graph-based architectures are becoming increasingly popular as a tool for structure generation. Here, we introduce a novel open-source archit
Fastest Gephi's ForceAtlas2 graph layout algorithm implemented for Python and NetworkX
ForceAtlas2 for Python A port of Gephi's Force Atlas 2 layout algorithm to Python 2 and Python 3 (with a wrapper for NetworkX and igraph). This is the
A Python wrapper API for operating and working with the Neo4j Graph Data Science (GDS) library
gdsclient NOTE: This is a work in progress and many GDS features are known to be missing or not working properly. This repo hosts the sources for gdsc
A Python wrapper API for operating and working with the Neo4j Graph Data Science (GDS) library
gdsclient This repo hosts the sources for gdsclient, a Python wrapper API for operating and working with the Neo4j Graph Data Science (GDS) library. g
Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes
Naive-Bayes Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes Downloading Data Set Use our Breast Cancer Wisconsin Data Set Also you can
Sentiment Analysis web app using Streamlit - American Airlines Tweets
Analyse des sentiments à partir des Tweets L'application est développée par Streamlit L'analyse sentimentale est effectuée sur l'ensemble de données d
PyTorch implementation for our AAAI 2022 Paper "Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning"
deepGCFX PyTorch implementation for our AAAI 2022 Paper "Graph-wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning" Pr
Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"
Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching This repository is an official implementation of
Neural network for digit classification powered by cuda
cuda_nn_mnist Neural network library for digit classification powered by cuda Resources The library was built to work with MNIST dataset. python-mnist
Classification of ecg datas for disease detection
ecg_classification Classification of ecg datas for disease detection
Malware-Related Sentence Classification
Malware-Related Sentence Classification This repo contains the code for the ICTAI 2021 paper "Enrichment of Features for Malware-Related Sentence Clas
Code for 2021 NeurIPS --- Towards Multi-Grained Explainability for Graph Neural Networks
ReFine: Multi-Grained Explainability for GNNs This is the official code for Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 20
Wav2Vec for speech recognition, classification, and audio classification
Soxan در زبان پارسی به نام سخن This repository consists of models, scripts, and notebooks that help you to use all the benefits of Wav2Vec 2.0 in your
Arabic speech recognition, classification and text-to-speech.
klaam Arabic speech recognition, classification and text-to-speech using many advanced models like wave2vec and fastspeech2. This repository allows tr
Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors
SSL_OSC Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors
A PyTorch based deep learning library for drug pair scoring.
Documentation | External Resources | Datasets | Examples ChemicalX is a deep learning library for drug-drug interaction, polypharmacy side effect and
The code written during my Bachelor Thesis "Classification of Human Whole-Body Motion using Hidden Markov Models".
This code was written during the course of my Bachelor thesis Classification of Human Whole-Body Motion using Hidden Markov Models. Some things might
Automatic detection and classification of Covid severity degree in LUS (lung ultrasound) scans
Final-Project Final project in the Technion, Biomedical faculty, by Mor Ventura, Dekel Brav & Omri Magen. Subproject 1: Automatic Detection of LUS Cha
Healthsea is a spaCy pipeline for analyzing user reviews of supplementary products for their effects on health.
Welcome to Healthsea ✨ Create better access to health with spaCy. Healthsea is a pipeline for analyzing user reviews to supplement products by extract
HTTP graph database built in Python 3
KiwiDB HTTP graph database built in Python 3. Reference Format References are strings in the format: {refIDENTIFIER@GROUP} Authentication Currently, t
Code for: Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification
Imagine by Reasoning: A Reasoning-Based Implicit Semantic Data Augmentation for Long-Tailed Classification Prerequisite PyTorch = 1.2.0 Python3 torch
Rethinking Nearest Neighbors for Visual Classification
Rethinking Nearest Neighbors for Visual Classification arXiv Environment settings Check out scripts/env_setup.sh Setup data Download the following fin
[ICCV 2021] Target Adaptive Context Aggregation for Video Scene Graph Generation
Target Adaptive Context Aggregation for Video Scene Graph Generation This is a PyTorch implementation for Target Adaptive Context Aggregation for Vide
Code for the ICCV'21 paper "Context-aware Scene Graph Generation with Seq2Seq Transformers"
ICCV'21 Context-aware Scene Graph Generation with Seq2Seq Transformers Authors: Yichao Lu*, Himanshu Rai*, Cheng Chang*, Boris Knyazev†, Guangwei Yu,
A machine learning web application for binary classification using streamlit
Machine Learning web App This is a machine learning web application for binary classification using streamlit options this application contains 3 clas
Working demo of the Multi-class and Anomaly classification model using the CLIP feature space
👁️ Hindsight AI: Crime Classification With Clip About For Educational Purposes Only This is a recursive neural net trained to classify specific crime
Library extending Jupyter notebooks to integrate with Apache TinkerPop and RDF SPARQL.
Graph Notebook: easily query and visualize graphs The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Us
A Persistent Embedded Graph Database for Python
Cog - Embedded Graph Database for Python cogdb.io New release: 2.0.5! Installing Cog pip install cogdb Cog is a persistent embedded graph database im
Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms
FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,
Edge-Augmented Graph Transformer
Edge-augmented Graph Transformer Introduction This is the official implementation of the Edge-augmented Graph Transformer (EGT) as described in https:
Test finetuning of XLSR (multilingual wav2vec 2.0) for other speech classification tasks
wav2vec_finetune Test finetuning of XLSR (multilingual wav2vec 2.0) for other speech classification tasks Initial test: gender recognition on this dat