674 Repositories
Python neighborhood-graph Libraries
Graph Neural Networks for Recommender Systems
This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library (DGL).
SpikeX - SpaCy Pipes for Knowledge Extraction
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.
Y. Zhang, Q. Yao, W. Dai, L. Chen. AutoSF: Searching Scoring Functions for Knowledge Graph Embedding. IEEE International Conference on Data Engineering (ICDE). 2020
AutoSF The code for our paper "AutoSF: Searching Scoring Functions for Knowledge Graph Embedding" and this paper has been accepted by ICDE2020. News:
Few-Shot Graph Learning for Molecular Property Prediction
Few-shot Graph Learning for Molecular Property Prediction Introduction This is the source code and dataset for the following paper: Few-shot Graph Lea
Knowledge Graph,Question Answering System,基于知识图谱和向量检索的医疗诊断问答系统
Knowledge Graph,Question Answering System,基于知识图谱和向量检索的医疗诊断问答系统
Official implementation of GraphMask as presented in our paper Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking.
GraphMask This repository contains an implementation of GraphMask, the interpretability technique for graph neural networks presented in our ICLR 2021
A Python library created to assist programmers with complex mathematical functions
libmaths libmaths was created not only as a learning experience for me, but as a way to make mathematical models in seconds for Python users using mat
Scalable Graph Neural Networks for Heterogeneous Graphs
Neighbor Averaging over Relation Subgraphs (NARS) NARS is an algorithm for node classification on heterogeneous graphs, based on scalable neighbor ave
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control
QA-GNN: Question Answering using Language Models and Knowledge Graphs
QA-GNN: Question Answering using Language Models and Knowledge Graphs This repo provides the source code & data of our paper: QA-GNN: Reasoning with L
Domain Connectivity Analysis Tools to analyze aggregate connectivity patterns across a set of domains during security investigations
DomainCAT (Domain Connectivity Analysis Tool) Domain Connectivity Analysis Tool is used to analyze aggregate connectivity patterns across a set of dom
Elliot is a comprehensive recommendation framework that analyzes the recommendation problem from the researcher's perspective.
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
peartree: A library for converting transit data into a directed graph for sketch network analysis.
peartree 🍐 🌳 peartree is a library for converting GTFS feed schedules into a representative directed network graph. The tool uses Partridge to conve
Tools for the extraction of OpenStreetMap street network data
OSMnet Tools for the extraction of OpenStreetMap (OSM) street network data. Intended to be used in tandem with Pandana and UrbanAccess libraries to ex
PyTorch code for the paper "Curriculum Graph Co-Teaching for Multi-target Domain Adaptation" (CVPR2021)
PyTorch code for the paper "Curriculum Graph Co-Teaching for Multi-target Domain Adaptation" (CVPR2021) This repo presents PyTorch implementation of M
The implementation of the CVPR2021 paper "Structure-Aware Face Clustering on a Large-Scale Graph with 10^7 Nodes"
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
Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution
FAU Implementation of the paper: Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution. Yingruo
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
Official implementation of Rethinking Graph Neural Architecture Search from Message-passing (CVPR2021)
Rethinking Graph Neural Architecture Search from Message-passing Intro The GNAS can automatically learn better architecture with the optimal depth of
Code for the paper "Graph Attention Tracking". (CVPR2021)
SiamGAT 1. Environment setup This code has been tested on Ubuntu 16.04, Python 3.5, Pytorch 1.2.0, CUDA 9.0. Please install related libraries before r
Code for paper "A Critical Assessment of State-of-the-Art in Entity Alignment" (https://arxiv.org/abs/2010.16314)
A Critical Assessment of State-of-the-Art in Entity Alignment This repository contains the source code for the paper A Critical Assessment of State-of
Spectral Temporal Graph Neural Network (StemGNN in short) for Multivariate Time-series Forecasting
Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting This repository is the official implementation of Spectral Temporal Gr
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
cuGraph - RAPIDS Graph Analytics Library
cuGraph - GPU Graph Analytics The RAPIDS cuGraph library is a collection of GPU accelerated graph algorithms that process data found in GPU DataFrames
Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization
CoMatch: Semi-supervised Learning with Contrastive Graph Regularization (Salesforce Research) This is a PyTorch implementation of the CoMatch paper [B
Official code for the paper: Deep Graph Matching under Quadratic Constraint (CVPR 2021)
QC-DGM This is the official PyTorch implementation and models for our CVPR 2021 paper: Deep Graph Matching under Quadratic Constraint. It also contain
We have implemented shaDow-GNN as a general and powerful pipeline for graph representation learning. For more details, please find our paper titled Deep Graph Neural Networks with Shallow Subgraph Samplers, available on arXiv (https//arxiv.org/abs/2012.01380).
Deep GNN, Shallow Sampling Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor Prasanna, Long Jin, R
Open Source research tool to search, browse, analyze and explore large document collections by Semantic Search Engine and Open Source Text Mining & Text Analytics platform (Integrates ETL for document processing, OCR for images & PDF, named entity recognition for persons, organizations & locations, metadata management by thesaurus & ontologies, search user interface & search apps for fulltext search, faceted search & knowledge graph)
Open Semantic Search https://opensemanticsearch.org Integrated search server, ETL framework for document processing (crawling, text extraction, text a
[CIKM 2019] Code and dataset for "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction"
FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti
A spherical CNN for weather forecasting
DeepSphere-Weather - Deep Learning on the sphere for weather/climate applications. The code in this repository provides a scalable and flexible framew
Implicit Graph Neural Networks
Implicit Graph Neural Networks This repository is the official PyTorch implementation of "Implicit Graph Neural Networks". Fangda Gu*, Heng Chang*, We
Learning Intents behind Interactions with Knowledge Graph for Recommendation, WWW2021
Learning Intents behind Interactions with Knowledge Graph for Recommendation This is our PyTorch implementation for the paper: Xiang Wang, Tinglin Hua
Functional TensorFlow Implementation of Singular Value Decomposition for paper Fast Graph Learning
tf-fsvd TensorFlow Implementation of Functional Singular Value Decomposition for paper Fast Graph Learning with Unique Optimal Solutions Cite If you f
Official implementation of Self-supervised Graph Attention Networks (SuperGAT), ICLR 2021.
SuperGAT Official implementation of Self-supervised Graph Attention Networks (SuperGAT). This model is presented at How to Find Your Friendly Neighbor
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
Graph Neural Networks with Keras and Tensorflow 2.
Welcome to Spektral Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to
Geometric Deep Learning Extension Library for PyTorch
Documentation | Paper | Colab Notebooks | External Resources | OGB Examples PyTorch Geometric (PyG) is a geometric deep learning extension library for
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
EGNN - Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch
EGNN - Pytorch Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch. May be eventually used for Alphafold2 replication. This
Implementation of E(n)-Transformer, which extends the ideas of Welling's E(n)-Equivariant Graph Neural Network to attention
E(n)-Equivariant Transformer (wip) Implementation of E(n)-Equivariant Transformer, which extends the ideas from Welling's E(n)-Equivariant G
A Python library created to assist programmers with complex mathematical functions
libmaths was created not only as a learning experience for me, but as a way to make mathematical models in seconds for Python users using mat
This repository contains the code used for Predicting Patient Outcomes with Graph Representation Learning (https://arxiv.org/abs/2101.03940).
Predicting Patient Outcomes with Graph Representation Learning This repository contains the code used for Predicting Patient Outcomes with Graph Repre
Generate a roam research like Network Graph view from your Notion pages.
Notion Graph View Export Notion pages to a Roam Research like graph view.
A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing"
A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf 2021). Abstract In this work we propose Pathfind
Official PyTorch implementation of Joint Object Detection and Multi-Object Tracking with Graph Neural Networks
This is the official PyTorch implementation of our paper: "Joint Object Detection and Multi-Object Tracking with Graph Neural Networks". Our project website and video demos are here.
A command line utility for tracking a stock market portfolio. Primarily featuring high resolution braille graphs.
A command line stock market / portfolio tracker originally insipred by Ericm's Stonks program, featuring unicode for incredibly high detailed graphs even in a terminal.
Plots is a graph plotting app for GNOME.
Plots is a graph plotting app for GNOME. Plots makes it easy to visualise mathematical formulae. In addition to basic arithmetic operations, it supports trigonometric, hyperbolic, exponential and logarithmic functions, as well as arbitrary sums and products.Plots is designed to integrate well with the GNOME desktop and takes advantage of modern hardware using OpenGL, and currently supports OpenGL 3.3+.
Python implementation of TextRank for phrase extraction and summarization of text documents
PyTextRank PyTextRank is a Python implementation of TextRank as a spaCy pipeline extension, used to: extract the top-ranked phrases from text document
The interactive graphing library for Python (includes Plotly Express) :sparkles:
plotly.py Latest Release User forum PyPI Downloads License Data Science Workspaces Our recommended IDE for Plotly’s Python graphing library is Dash En
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.
Python implementation of TextRank for phrase extraction and summarization of text documents
PyTextRank PyTextRank is a Python implementation of TextRank as a spaCy pipeline extension, used to: extract the top-ranked phrases from text document
The interactive graphing library for Python (includes Plotly Express) :sparkles:
plotly.py Latest Release User forum PyPI Downloads License Data Science Workspaces Our recommended IDE for Plotly’s Python graphing library is Dash En
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply
Overview | Tutorials | Examples | Installation | FAQ | How to Cite Welcome to ktrain News and Announcements 2020-11-08: ktrain v0.25.x is released and
Visual profiler for Python
vprof vprof is a Python package providing rich and interactive visualizations for various Python program characteristics such as running time and memo
:package: :fire: Python project management. Manage packages: convert between formats, lock, install, resolve, isolate, test, build graph, show outdated, audit. Manage venvs, build package, bump version.
THE PROJECT IS ARCHIVED Forks: https://github.com/orsinium/forks DepHell -- project management for Python. Why it is better than all other tools: Form
A Static Analysis Tool for Detecting Security Vulnerabilities in Python Web Applications
This project is no longer maintained March 2020 Update: Please go see the amazing Pysa tutorial that should get you up to speed finding security vulne
Neo4j Bolt driver for Python
Neo4j Bolt Driver for Python This repository contains the official Neo4j driver for Python. Each driver release (from 4.0 upwards) is built specifical
Python library for serializing any arbitrary object graph into JSON. It can take almost any Python object and turn the object into JSON. Additionally, it can reconstitute the object back into Python.
jsonpickle jsonpickle is a library for the two-way conversion of complex Python objects and JSON. jsonpickle builds upon the existing JSON encoders, s
A python module to parse the Open Graph Protocol
OpenGraph is a module of python for parsing the Open Graph Protocol, you can read more about the specification at http://ogp.me/ Installation $ pip in
Facebook open graph api implementation using the Django web framework in python
Django Facebook by Thierry Schellenbach (mellowmorning.com) Status Django and Facebook are both rapidly changing at the moment. Meanwhile, I'm caught
This is a simple graph database in SQLite, inspired by
This is a simple graph database in SQLite, inspired by "SQLite as a document database".
Graph Transformer Architecture. Source code for
Graph Transformer Architecture Source code for the paper "A Generalization of Transformer Networks to Graphs" by Vijay Prakash Dwivedi and Xavier Bres
Transformers are Graph Neural Networks!
🚀 Gated Graph Transformers Gated Graph Transformers for graph-level property prediction, i.e. graph classification and regression. Associated article
Graph neural network message passing reframed as a Transformer with local attention
Adjacent Attention Network An implementation of a simple transformer that is equivalent to graph neural network where the message passing is done with
Official PyTorch implementation for paper Context Matters: Graph-based Self-supervised Representation Learning for Medical Images
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images Official PyTorch implementation for paper Context Matters: Gra
Python SDK for Facebook's Graph API
Facebook Python SDK This client library is designed to support the Facebook Graph API and the official Facebook JavaScript SDK, which is the canonical
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
StellarGraph - Machine Learning on Graphs
StellarGraph Machine Learning Library StellarGraph is a Python library for machine learning on graphs and networks. Table of Contents Introduction Get
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour
A Temporal Extension Library for PyTorch Geometric
Documentation | External Resources | Datasets PyTorch Geometric Temporal is a temporal (dynamic) extension library for PyTorch Geometric. The library
Visual profiler for Python
vprof vprof is a Python package providing rich and interactive visualizations for various Python program characteristics such as running time and memo
Minimal examples of data structures and algorithms in Python
Pythonic Data Structures and Algorithms Minimal and clean example implementations of data structures and algorithms in Python 3. Contributing Thanks f