Python Graph-algorithms Resources

Reinforcement Learning (PyTorch) 🤖 + 🍰 = ❤️ This repo will contain PyTorch implementation of various fundamental RL algorithms. It's aimed at making

python_graphs This package is for computing graph representations of Python programs for machine learning applications. It includes the following modu

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

PairRE Code for paper PairRE: Knowledge Graph Embeddings via Paired Relation Vectors. This implementation of PairRE for Open Graph Benchmak datasets (

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

Visual Tracking by TridentAlign and Context Embedding (TACT) Test code for "Visual Tracking by TridentAlign and Context Embedding" Janghoon Choi, Juns

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks Molecular interaction networks are powerful resources for the discovery. While dee

A Closer Look at Invalid Action Masking in Policy Gradient Algorithms This repo contains the source code to reproduce the results in the paper A Close

Graph-Based Protein Design This repo contains code for Generative Models for Graph-Based Protein Design by John Ingraham, Vikas Garg, Regina Barzilay

Desmos Bezier Renderer A simple image/video to Desmos graph converter run locally Sample Result Setup Install dependencies apt update apt install git

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform

Implementation of different ML Algorithms from scratch, written in Python 3.x

Algo Drills A command line tool for memorizing algorithms in Python by typing them. In alpha and things will change. How it works Type out an algorith

Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs Jiong Zhu, Yujun Yan, Lingxiao Zhao, Mark Heimann, Leman Akoglu,

Graph Evolving Meta-Learning for Low-resource Medical Dialogue Generation Code to be further cleaned... This repo contains the code of the following p

Speech Algorithms Collections

MADGRAD Optimization Algorithm For Tensorflow This package implements the MadGrad Algorithm proposed in Adaptivity without Compromise: A Momentumized,

Introduction This is the PyTorch implementation for Adaptive Graph Representation Learning for Video Person Re-identification. Get started git clone h

Learning Knowledge Bases with Parameters for Task-Oriented Dialogue Systems This is the implementation of the paper: Learning Knowledge Bases with Par

End-to-End Optimization of Scene Layout Code release for: End-to-End Optimization of Scene Layout CVPR 2020 (Oral) Project site, Bibtex For help conta

PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-based API design, PyKale enforces standardization and minimalism, via reusing existing resources, reducing repetitions and redundancy, and recycling learning models across areas.

coax is built on top of JAX, but it doesn't have an explicit dependence on the jax python package. The reason is that your version of jaxlib will depend on your CUDA version.

This repository contains code to train and test GNN models for recommendation, mainly using the Deep Graph Library (DGL).

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.

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 Introduction This is the source code and dataset for the following paper: Few-shot Graph Lea

mbrl-lib is a toolbox for facilitating development of Model-Based Reinforcement Learning algorithms. It provides easily interchangeable modeling and planning components, and a set of utility functions that allow writing model-based RL algorithms with only a few lines of code.

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

GraphMask This repository contains an implementation of GraphMask, the interpretability technique for graph neural networks presented in our ICLR 2021

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

LiuAlgoTrader is a scalable, multi-process ML-ready framework for effective algorithmic trading. The framework simplify development, testing, deployment, analysis and training algo trading strategies. The framework automatically analyzes trading sessions, and the analysis may be used to train predictive models.

Neighbor Averaging over Relation Subgraphs (NARS) NARS is an algorithm for node classification on heterogeneous graphs, based on scalable neighbor ave

Faster R-CNN and Mask R-CNN in PyTorch 1.0 maskrcnn-benchmark has been deprecated. Please see detectron2, which includes implementations for all model

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

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

AdvancedHMC.jl AdvancedHMC.jl provides a robust, modular and efficient implementation of advanced HMC algorithms. An illustrative example for Advanced

The SLIDE package contains the source code for reproducing the main experiments in this paper. Dataset The Datasets can be downloaded in Amazon-

DomainCAT (Domain Connectivity Analysis Tool) Domain Connectivity Analysis Tool is used to analyze aggregate connectivity patterns across a set of dom

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

Project Overview Stock market movement prediction using LSTM Deep Neural Networks and machine learning algorithms Software and Library Requirements Th

StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both

TradzQAI Trading environnement for RL agents, backtesting and training. Live session with coinbasepro-python is finaly arrived ! Available sessions: L

Trading Gym Trading Gym is an open-source project for the development of reinforcement learning algorithms in the context of trading. It is currently

peartree 🍐 🌳 peartree is a library for converting GTFS feed schedules into a representative directed network graph. The tool uses Partridge to conve

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) This repo presents PyTorch implementation of M

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

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.

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

A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)

Rethinking Graph Neural Architecture Search from Message-passing Intro The GNAS can automatically learn better architecture with the optimal depth of

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

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 for Multivariate Time-series Forecasting This repository is the official implementation of Spectral Temporal Gr

Markov Decision Process A Markov decision process (MDP), by definition, is a sequential decision problem for a fully observable, stochastic environmen

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

A variety of matrix completion and imputation algorithms implemented in Python 3.6. To install: pip install fancyimpute Do not use conda. We don't sup

scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A

cuGraph - GPU Graph Analytics The RAPIDS cuGraph library is a collection of GPU accelerated graph algorithms that process data found in GPU DataFrames

cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t

cuDF - GPU DataFrames NOTE: For the latest stable README.md ensure you are on the main branch. Resources cuDF Reference Documentation: Python API refe

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

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

Surpriver - Find High Moving Stocks before they Move Find high moving stocks before they move using anomaly detection and machine learning. Surpriver

Backtesting.py Backtest trading strategies with Python. Project website Documentation the project if you use it. Installation $ pip install backtestin

FinTA (Financial Technical Analysis) Common financial technical indicators implemented in Pandas. This is work in progress, bugs are expected and resu

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

PG-MORL This repository contains the implementation for the paper Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Contro

Open-L2O This repository establishes the first comprehensive benchmark efforts of existing learning to optimize (L2O) approaches on a number of proble

QC-DGM This is the official PyTorch implementation and models for our CVPR 2021 paper: Deep Graph Matching under Quadratic Constraint. It also contain

Deep GNN, Shallow Sampling Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor Prasanna, Long Jin, R

Open Semantic Search https://opensemanticsearch.org Integrated search server, ETL framework for document processing (crawling, text extraction, text a

PRLib - Pre-Recognition Library. The main aim of the library - prepare image for recogntion. Image processing can really help to improve recognition q

Scene Text Localization & Recognition Resources Read this institute-wise: English, 简体中文. Read this year-wise: English, 简体中文. Tags: [STL] (Scene Text L

Typefont Typefont is an experimental library that detects the font of a text in a image. Usage Import the main function and invoke it like in the foll

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

DeepSphere-Weather - Deep Learning on the sphere for weather/climate applications. The code in this repository provides a scalable and flexible framew

Enjoy-Hamburger 🍔 Official implementation of Hamburger, Is Attention Better Than Matrix Decomposition? (ICLR 2021) Under construction. Introduction T

Implicit Graph Neural Networks This repository is the official PyTorch implementation of "Implicit Graph Neural Networks". Fangda Gu*, Heng Chang*, We

Algojammer Algojammer is an experimental, proof-of-concept code editor for writing algorithms in Python. It was mainly written to assist with solving

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

Learning Intents behind Interactions with Knowledge Graph for Recommendation This is our PyTorch implementation for the paper: Xiang Wang, Tinglin Hua

PGPElib A mini library for Policy Gradients with Parameter-based Exploration [1] and friends. This library serves as a clean re-implementation of the

tf-fsvd TensorFlow Implementation of Functional Singular Value Decomposition for paper Fast Graph Learning with Unique Optimal Solutions Cite If you f

SuperGAT Official implementation of Self-supervised Graph Attention Networks (SuperGAT). This model is presented at How to Find Your Friendly Neighbor

Data Structures and Algorithms Python INDEX 1. Resources - Books Data Structures - Reema Thareja competitiveCoding Big-O Cheat Sheet DAA Syllabus Inte

MAPPO Chao Yu*, Akash Velu*, Eugene Vinitsky, Yu Wang, Alexandre Bayen, and Yi Wu. Website: https://sites.google.com/view/mappo This repository implem

Algo-ScriptML Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The goal of this project is not t

NLopt is a library for nonlinear local and global optimization, for functions with and without gradient information. It is designed as a simple, unifi

PySwarms is an extensible research toolkit for particle swarm optimization (PSO) in Python. It is intended for swarm intelligence researchers, practit

Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not

sklearn-deap Use evolutionary algorithms instead of gridsearch in scikit-learn. This allows you to reduce the time required to find the best parameter

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

Dopamine Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grok

TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning. TF-Agents makes implementing, de

Stable Baselines Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines. You can read a

Status: Maintenance (expect bug fixes and minor updates) Baselines OpenAI Baselines is a set of high-quality implementations of reinforcement learning

Master status: Development status: Package information: scikit-rebate This package includes a scikit-learn-compatible Python implementation of ReBATE,