Python Graph-algorithms Resources

GSAN Introduction Code for paper GSAN: Graph Self-Attention Network for Learning Spatial-Temporal Interaction Representation in Autonomous Driving, wh

ts2vg: Time series to visibility graphs The Python ts2vg package provides high-performance algorithm implementations to build visibility graphs from t

PLUR (Programming-Language Understanding and Repair) is a collection of source code datasets suitable for graph-based machine learning. We provide scripts for downloading, processing, and loading the datasets. This is done by offering a unified API and data structures for all datasets.

Convenient script for trading with python.

#Sentic GCN Introduction This repository was used in our paper: Aspect-Based Sentiment Analysis via Affective Knowledge Enhanced Graph Convolutional N

multilingual-mrc-isdg Code for the AAAI 2022 paper "Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph". This r

Self-Supervised Graph Representation Learning via Topology Transformations This repository is the official PyTorch implementation of the following pap

decentralized-gnn A package for implementing and simulating decentralized Graph Neural Network algorithms for classification of peer-to-peer nodes. De

Decoding the Protein-ligand Interactions Using Parallel Graph Neural Networks Requirements python 0.10+ rdkit 2020.03.3.0 biopython 1.78 openbabel 2.4

Adversarial Attacks on Graph Classification via Bayesian Optimisation @ NeurIPS 2021 This repository contains the official implementation of GRABNEL,

Discovering Dynamic Salient Regions with Spatio-Temporal Graph Neural Networks This is the official code for DyReg model inroduced in Discovering Dyna

Graph Neural Topic Model (GNTM) This is the pytorch implementation of the paper "Topic Modeling Revisited: A Document Graph-based Neural Network Persp

Graph Augmentation Graph augmentation/self-supervision/etc. Algorithms gcn gcn+virtual node gin gin+virtual node PNA GraphTrans Augmentation methods N

ReFine: Multi-Grained Explainability for GNNs We are trying hard to update the code, but it may take a while to complete due to our tight schedule rec

EIGNN: Efficient Infinite-Depth Graph Neural Networks The official implementation of EIGNN: Efficient Infinite-Depth Graph Neural Networks (NeurIPS 20

Directed Graph Contrastive Learning Paper | Poster | Supplementary The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this

Code for "Solving Graph-based Public Good Games with Tree Search and Imitation Learning" This is the code for the paper Solving Graph-based Public Goo

PyDGN Wiki Description This is a Python library to easily experiment with Deep Graph Networks (DGNs). It provides automatic management of data splitti

Visualisation for sorting algorithms v2. Upped a notch from version 1. This program provides animates simple, common and popular sorting algorithms, t

Algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex)

Cutting Stock Problem Cutting Stock Problem (CSP) deals with planning the cutting of items (rods / sheets) from given stock items (which are usually o

MatrixProfile MatrixProfile is a Python 3 library, brought to you by the Matrix Profile Foundation, for mining time series data. The Matrix Profile is

Short Text Mining in Python Introduction This package shorttext is a Python package that facilitates supervised and unsupervised learning for short te

ESP32-IoT-button-graph-test ESP32 recording button presses, and serving webpage via webSockets in order to graph the responses. The objective was to t

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model This repository is the official PyTorch implementation of GraphRNN, a graph gene

Unbiased Learning to Rank Algorithms (ULTRA) This is an Unbiased Learning To Rank Algorithms (ULTRA) toolbox, which provides a codebase for experiment

KDD CUP 2020: AutoGraph Team: aister Members: Jianqiang Huang, Xingyuan Tang, Mingjian Chen, Jin Xu, Bohang Zheng, Yi Qi, Ke Hu, Jun Lei Team Introduc

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

PathPlanningAlgorithms It is a platform that implements some path planning algorithms. Main dependence: python3.7, opencv4.1.1.26 (for image show) Tip

🔍 E-Commerce recommender demo 🔍 This is a simple stream setup that uses Memgraph to ingest real-time data from a simulated online store. Data is str

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

awesome-causality-algorithms An index of algorithms for learning causality with data. Please cite our survey paper if this index is helpful. @article{

OANet implementation Pytorch implementation of OANet for ICCV'19 paper "Learning Two-View Correspondences and Geometry Using Order-Aware Network", by

Calculator 🖩 A simple calculator written in python allows you to make simple calculations, write charts, calculate the dates, and exchange currency.

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

SPTAG: A library for fast approximate nearest neighbor search SPTAG SPTAG (Space Partition Tree And Graph) is a library for large scale vector approxi

This repository holds the implementation for paper Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach Download our preproc

RSL RL Fast and simple implementation of RL algorithms, designed to run fully on GPU. This code is an evolution of rl-pytorch provided with NVIDIA's I

Parameterized Hypercomplex Graph Neural Networks (PHC-GNNs) PHC-GNNs (Le et al., 2021): https://arxiv.org/abs/2103.16584 PHM Linear Layer Illustration

SSR (NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductivefew-shot classification" [Paper] [Project webpage]

SAGCN - Official PyTorch Implementation | Paper | Project Page This is the official implementation of the paper "Steganographer detection via a simila

g2o - General Graph Optimization Linux: Windows: g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions. g2o has bee

Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera

ApproxMVBB Status Build UnitTests Homepage Fast algorithms to compute an approximation of the minimal volume oriented bounding box of a point cloud in

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

Orbitals in Python A small collection of tools made by me, that you can use to visualize atomic orbitals in both 2D and 3D in different aspects, and o

SURGE: Sequential Recommendation with Graph Neural Networks This is our TensorFlow implementation for the paper: Sequential Recommendation with Graph

MassFormer This is the original implementation of MassFormer, a graph transformer for small molecule MS/MS prediction. Check out the preprint on arxiv

ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard We

Dynamic-Graphs-Construction Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Ne

2s-AGCN Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19 Note PyTorch version should be 0.3! For PyTor

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

Fine-grained Sentiment Analysis as Dependency Graph Parsing This repository contains the code and datasets described in following paper: Fine-grained

SwisE Switch spaces for knowledge graph embeddings. Requirements: python3 pytorch numpy tqdm Reproduce the results To reproduce the reported results,

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

moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar

Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF

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

Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.

forest-confidence-interval: Confidence intervals for Forest algorithms Forest algorithms are powerful ensemble methods for classification and regressi

A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow

pybullet-planning (previously ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and

Overview of OpenPNM OpenPNM is a comprehensive framework for performing pore network simulations of porous materials. More Information For more detail

Pigment The problem of partitioning up a skincare regime into parts such that each part does not interfere with itself is equivalent to the minimal cl

Code has been run on Google Colab, thanks Google for providing computational resources Contents Natural Language Processing（自然语言处理） Text Classificati

music-recommender-rest-api A music recommendation REST API which makes a machine learning algorithm work with the Django REST Framework How it works T

Diabetes Disease Prediction This is a machine Learning mode which tries to determine if a person has a diabetes or not. Data The dataset is in comma s

Problems and it's solutions. Problem solving, a great Speed comes with a good Accuracy. The more Accurate you can write code, the more Speed you will

Differential_Privacy_CPS Python implementation of the research paper Leveraging Unique CPS Properties to Design Better Privacy-Enhancing Algorithms Re

iAWE is a wonderful dataset for those of us who work on Non-Intrusive Load Monitoring (NILM) algorithms. You can find its main page and description via this link. If you are familiar with NILM-TK API, you probably know that you can work with iAWE hdf5 data file in NILM-TK.

A place to post ideas, partial projects, or anything else that doesn't necessarily warrant its own repo, from my mind to the web.

Ohm-s-Law-Visualizer It's an application to calculate I from v and r using Ohm's Law. It can also plot a graph between V vs I. Story I'm doing my Unde

Implementing Graph Convolutional Networks and Information Retrieval Mechanisms using pure Python and NumPy

Visualization of numerical optimization algorithms

CleanRL (Clean Implementation of RL Algorithms) CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation

GN-Transformer AST This is the official repository for the paper "GN-Transformer: Fusing AST and Source Code information in Graph Networks". Data Prep

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

orqviz A Python package for easily visualizing the loss landscape of Variational Quantum Algorithms by Zapata Computing Inc. orqviz provides a collect

GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network

TensorFlow GNN This is an early (alpha) release to get community feedback. It's under active development and we may break API compatibility in the fut

HashDB HashDB is a community-sourced library of hashing algorithms used in malware. How To Use HashDB HashDB can be used as a stand alone hashing libr

Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.

Housegan-data-reader House-GAN++ (data-reader) Code and instructions for converting rplan dataset (raster images) to housegan++ data format. House-GAN

Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact [email protected] for comments a

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

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

GENDIS GENetic DIscovery of Shapelets In the time series classification domain, shapelets are small subseries that are discriminative for a certain cl

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

Machine learning algorithms implementation This repository consisits of implementation of various machine learning algorithms. The algorithms implemen

Time2box Implementation of [Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes].

HaloGraphNet Predict halo masses from simulations via Graph Neural Networks. Given a dark matter halo and its galaxies, creates a graph with informati

Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?

Interactive Web App with Streamlit and Scikit-learn that applies different Classification algorithms to popular datasets Datasets Used: Iris dataset,

Introduction MASS allows you to search a time series for a subquery resulting in an array of distances. These array of distances enable you to identif

Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

Evol is clear dsl for composable evolutionary algorithms that optimised for joy. Installation We currently support python3.6 and python3.7 and you can

onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o