Python Graph-attention Resources

This repository is an official PyTorch(Geometric) implementation of G^2GNN in "Imbalanced Graph Classification via Graph-of-Graph Neural Networks". Th

Efficient Graph Similarity Computation - (EGSC) This repo contains the source code and dataset for our paper: Slow Learning and Fast Inference: Effici

Knowledge-enhanced Contrastive Learning (KCL) Molecular Contrastive Learning with Chemical Element Knowledge Graph [ AAAI 2022 ]. We construct a Chemi

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.

NLP-GPT-Upsampling This repository contains an implementation of Open AI's GPT Model. In particular, this implementation takes inspiration from the Ny

BERT Attention Analysis This repository contains code for What Does BERT Look At? An Analysis of BERT's Attention. It includes code for getting attent

The Story of Heads This is the official repo for the following papers: (ACL 2019) Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy

PyTorch implementation of BERT and PALs Introduction Work by Asa Cooper Stickland and Iain Murray, University of Edinburgh. Code for BERT and PALs; mo

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

Generative Image Inpainting An open source framework for generative image inpainting task, with the support of Contextual Attention (CVPR 2018) and Ga

Attention Is All You Need Paper Implementation This is my from-scratch implementation of the original transformer architecture from the following pape

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

Shunted Transformer This is the offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation by Sucheng Ren, Daquan Zhou, Shengf

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

PyContinual (An Easy and Extendible Framework for Continual Learning) Easy to Use You can sumply change the baseline, backbone and task, and then read

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

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

Subspace Adversarial Training Single-step adversarial training (AT) has received wide attention as it proved to be both efficient and robust. However,

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

Image Captioning using CNN ,LSTM and Attention This is a deeplearning model which tries to summarize an image into a text . Installation Install this

🔍 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

Image Super-Resolution Using Very Deep Residual Channel Attention Networks

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.

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

GCA-Matting: Natural Image Matting via Guided Contextual Attention The source codes and models of Natural Image Matting via Guided Contextual Attentio

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]

PCAN for Multiple Object Tracking and Segmentation This is the offical implementation of paper PCAN for MOTS. We also present a trailer that consists

CoaDTI Multi-modal co-attention for drug-target interaction annotation and Its Application to SARS-CoV-2 Abstract Environment The test was conducted i

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

DHF1K =========================================================================== Wenguan Wang, J. Shen, M.-M Cheng and A. Borji, Revisiting Video Sal

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

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,

DARP-SBIR Intro This repository contains the source code implementation for ICDM submission paper Deep Reinforced Attention Regression for Partial Ske

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

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

Codebase for "ProtoAttend: Attention-Based Prototypical Learning." Authors: Sercan O. Arik and Tomas Pfister Paper: Sercan O. Arik and Tomas Pfister,

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

faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2

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

nlp-tutorial is a tutorial for who is studying NLP(Natural Language Processing) using Pytorch. Most of the models in NLP were implemented with less than 100 lines of code.(except comments or blank lines)

hierarchical-multi-label-text-classification-pytorch Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach This

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

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

You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling Transformer-based models are widely used in natural language processi

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

RAANet: Range-Aware Attention Network for LiDAR-based 3D Object Detection with Auxiliary Density Level Estimation Anonymous submission Abstract 3D obj

DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis

SATGAN TODO: update the article URL once published. Article about this implemention The self-attentive task generative adversarial network (SATGAN) le

CoAtNet Overview This is a PyTorch implementation of CoAtNet specified in "CoAtNet: Marrying Convolution and Attention for All Data Sizes", arXiv 2021

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

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

astroheat Installation Requires Python 3.6+, Tested with Python 3.9.5 Install library dependencies pip install -r requirements.txt The program require

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

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

LHC-Net Local Multi-Head Channel Self-Attention This repository is intended to provide a quick implementation of the LHC-Net and to replicate the resu

This repo is built for paper: Attention Mechanisms in Computer Vision: A Survey paper Vision-Attention-Papers Channel attention Spatial attention Temp

"A Probabilistic Hard Attention Model For Sequentially Observed Scenes" Authors: Samrudhdhi Rangrej, James Clark Accepted to: BMVC'21 A recurrent atte

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?

Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta

EZ-Graph EZ Graph is a GUI that allows users to make and train neural networks without writing a single line of code. Requirements python 3 pandas num

Medical Image Segmentation with Guided Attention This repository contains the code of our paper: "'Multi-scale self-guided attention for medical image

PSANet: Point-wise Spatial Attention Network for Scene Parsing (in construction) by Hengshuang Zhao*, Yi Zhang*, Shu Liu, Jianping Shi, Chen Change Lo

CCNet: Criss-Cross Attention for Semantic Segmentation Paper Links: Our most recent TPAMI version with improvements and extensions (Earlier ICCV versi

Dual Attention Network for Scene Segmentation(CVPR2019) Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang,and Hanqing Lu Introduction W

Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor

Segmentation-Aware Convolutional Networks Using Local Attention Masks [Project Page] [Paper] Segmentation-aware convolution filters are invariant to b

pytorch Implementation of U-Net, R2U-Net, Attention U-Net, Attention R2U-Net U-Net: Convolutional Networks for Biomedical Image Segmentation https://a

GATER This repository contains the code for our EMNLP 2021 paper “Heterogeneous Graph Neural Networks for Keyphrase Generation”. Our implementation is

GraphWar: Arms Race in Graph Adversarial Learning NOTE: GraphWar is still in the early stages and the API will likely continue to change. 🚀 Installat