Python Graph-transformer Resources

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Figure 1: Performance of SegFormer-B0 to SegFormer-B5. Project page

[中文|English] Rotary Transformer Rotary Transformer is an MLM pre-trained language model with rotary position embedding (RoPE). The RoPE is a relative

Table of contents Mesh Transformer JAX Updates Pretrained Models GPT-J-6B Links Acknowledgments License Model Details Zero-Shot Evaluations Architectu

FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,

CPT This repository contains code and checkpoints for CPT. CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Gener

Edge-augmented Graph Transformer Introduction This is the official implementation of the Edge-augmented Graph Transformer (EGT) as described in https:

FastFormers FastFormers provides a set of recipes and methods to achieve highly efficient inference of Transformer models for Natural Language Underst

Sequential Transformer This is a code for training Transformers on sequential tasks such as language modeling. Unlike the original Transformer archite

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models

The KLEJ Benchmark Baselines The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language und

A State-of-the-Art Large-scale Pretrained Response Generation Model (DialoGPT) This repository contains the source code and trained model for a large-

transformer-sequential This repo contains the code for two papers: Feedback Transformer Expire-Span The training code is structured for long sequentia

Introduction Funnel-Transformer is a new self-attention model that gradually compresses the sequence of hidden states to a shorter one and hence reduc

Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz

Pay Attention when Required (PAR) Transformer-XL An implementation of the Pay Attention when Required transformer from the paper: https://arxiv.org/pd

Routing Transformer A fully featured implementation of Routing Transformer. The paper proposes using k-means to route similar queries / keys into the

Linear Multihead Attention (Linformer) PyTorch Implementation of reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer:

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

Longformer Longformer and LongformerEncoderDecoder (LED) are pretrained transformer models for long documents. ***** New December 1st, 2020: Longforme

Improving Transformer Models by Reordering their Sublayers This repository contains the code for running the character-level Sandwich Transformers fro

BP-Transformer This repo contains the code for our paper BP-Transformer: Modeling Long-Range Context via Binary Partition Zihao Ye, Qipeng Guo, Quan G

CTRL - A Conditional Transformer Language Model for Controllable Generation Authors: Nitish Shirish Keskar, Bryan McCann, Lav Varshney, Caiming Xiong,

💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️

CGPN This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels]. Req

Gihan Jayatilaka*, Jameel Hassan*, Suren Sritharan*, Janith Senananayaka, Harshana Weligampola, et. al., 2021. Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations. arXiv preprint.

Decentralised graph database management system To get started clone the repo, and run the command below. python3 database.py Now, create a new termina

Transformer for Image Colorization This is an implemention for Yes, "Attention Is All You Need", for Exemplar based Colorization, and the current soft

Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation in TensorFlow 2 Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexan

Docker Network Graph Visualize the relationship between Docker networks and containers as a neat graphviz graph. Example Usage usage: docker-net-graph

Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs This repository contains code to accompany the paper "Hierarchical Clustering: O

Dual Correlation Reduction Network An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022. Any

Sparse Structure Learning via Graph Neural Networks for inductive document classification Make graph dataset create co-occurrence graph for datasets.

How to apply? Create your config.ini file following the example provided in config.ini Choose one of the options below to run: Run with Python3 pip in

SHGNN: Structure-Aware Heterogeneous Graph Neural Network The source code and dataset of the paper: SHGNN: Structure-Aware Heterogeneous Graph Neural

Lambekseq "Everyone who failed Greek or Latin hates it." This package is for proving theorems in Categorial grammars (CG) and constructing semantic gr

SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer

BiCAT This is our TensorFlow implementation for the paper: "BiCAT: Sequential Recommendation with Bidirectional Chronological Augmentation of Transfor

Code data_preprocess.py: preprocess data for Dependent-T5. parameters.py: define parameters of Dependent-T5. train_tools.py: traning and evaluation co

RDFLib RDFLib is a pure Python package for working with RDF. RDFLib contains most things you need to work with RDF, including: parsers and serializers

PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.

# 1. Installing Maven & Pandas First, please install Java (JDK11) and Python 3 if they are not already. Next, make sure that Maven (for importing J

LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and

Contents AnonyGAN Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Evaluation Acknowledgments Citat

(Preprint) Official PyTorch implementation of "How Do Vision Transformers Work?"

t5-japanese Codes to pre-train T5 (Text-to-Text Transfer Transformer) models pre-trained on Japanese web texts. The following is a list of models that

Monte Carlo python simulation Install linux dependencies sudo apt update sudo apt install build-essential \ software-properties-commo

A Vision Transformer approach that uses concatenated query and reference images to learn the relationship between query and reference images directly.

CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation [arxiv] This is the official repository for CDTrans: Cross-domain Transformer for

KIDA: Knowledge Inheritance in Data Aggregation This project releases our 1st place solution on NeurIPS2021 ML4CO Dual Task. Slide and model weights a

PyTorch implementation of Video Transformer Benchmarks This repository is mainly built upon Pytorch and Pytorch-Lightning. We wish to maintain a colle

PyTorch implementation of Continuous Augmented Positional Embeddings (CAPE), by Likhomanenko et al. Enhance your Transformer positional embeddings with easy-to-use augmentations!

CogniPy for Pandas - In-memory Graph Database and Knowledge Graph with Natural Language Interface Whats in the box Reasoning, exploration of RDF/OWL,

Are Transformers More Robust Than CNNs? Pytorch implementation for NeurIPS 2021 Paper: Are Transformers More Robust Than CNNs? Our implementation is b

WSDM 2022 Large-scale Temporal Graph Link Prediction - Baseline and Initial Test Set WSDM Cup Website link Link to this challenge This branch offers A

SST: Single-stride Sparse Transformer This is the official implementation of paper: Embracing Single Stride 3D Object Detector with Sparse Transformer

HetGAN Implementation of Heterogeneous Graph Attention Network This is the code repository of paper "Prediction of Metro Ridership During the COVID-19

Knowledge Graph Embeddings and Chemical Effect Prediction, 2020. Scripts and outputs related to the paper Prediction of Adverse Biological Effects of

Enhancing Column Generation by a Machine-Learning-BasedPricing Heuristic for Graph Coloring (to appear at AAAI 2022) We propose a machine-learning-bas

AKGNN The source code for Adaptive Kernel Graph Neural Network at AAAI2022. Please cite our paper if you think our work is helpful to you: @inproceedi

Wikidated Wikidated 1.0 is a dataset of Wikidata’s full revision history, which encodes changes between Wikidata revisions as sets of deletions and ad

REGO-Deformable DETR By Zhe Chen, Jing Zhang, and Dacheng Tao. This repository is the implementation of the paper Recurrent Glimpse-based Decoder for

TransVTSpotter: End-to-end Video Text Spotter with Transformer Introduction A Multilingual, Open World Video Text Dataset and End-to-end Video Text Sp

DiffMG This repository contains the code for our KDD 2021 Research Track paper: DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neura

Introduction K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce. Installation PyTor

Trapper (Transformers wRAPPER) Trapper is an NLP library that aims to make it easier to train transformer based models on downstream tasks. It wraps h

PyCRE Conflict-aware Inference of Python Compatible Runtime Environments with Domain Knowledge Graph, ICSE 2022 Dependencies This project is developed

SimMIM By Zhenda Xie*, Zheng Zhang*, Yue Cao*, Yutong Lin, Jianmin Bao, Zhuliang Yao, Qi Dai and Han Hu*. This repo is the official implementation of

END TO END ASR TRANSFORMER 本项目基于transformer 6*encoder+6*decoder的基本结构构造的端到端的语音识别系统 Model Instructions 1.数据准备: 自行下载数据，遵循文件结构如下： ├── data │ ├── train │

LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and

CRGNN Paper ： Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090

Junction Tree Variational Autoencoder for Molecular Graph Generation Official implementation of our Junction Tree Variational Autoencoder https://arxi

MINERVA Meandering In Networks of Entities to Reach Verisimilar Answers Code and models for the paper Go for a Walk and Arrive at the Answer - Reasoni

CCasGNN A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics,

Graph Neural Controlled Differential Equations for Traffic Forecasting Setup Python environment for STG-NCDE Install python environment $ conda env cr

RaceBERT -- A transformer based model to predict race and ethnicty from names Installation pip install racebert Using a virtual environment is highly

Graph WaveNet for brain network analysis This is the implementation of the Graph WaveNet model used in our manuscript: S. Wein , A. Schüller, A. M. To

CRGNN Paper ： Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090

Transformer-in-Transformer An Implementation of the Transformer in Transformer paper by Han et al. for image classification, attention inside local pa

README Needs to be improved Prerequisites Need to have graphiz installed on the machine. Refer to https://graphviz.readthedocs.io/en/stable/manual.htm

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Papers about explainability of GNNs

subgraph-extractor Extracts data from the database for a graph-node and stores it in parquet files Installation For developing, it's recommended to us

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

MOVED TO HERE Spatial Transformer Networks Spatial Transformer Networks (STN) is a dynamic mechanism that produces transformations of input images (or

ASCII Graph Plotter Plots the graph of a function with ASCII characters. See the change log here. Developed by InformaticFreak (c) 2021 How to use py

PFD：Pose-guided Feature Disentangling for Occluded Person Re-identification based on Transformer This repo is the official implementation of "Pose-gui

Learning Tracking Representations via Dual-Branch Fully Transformer Networks DualTFR ⭐ We achieves the runner-ups for both VOT2021ST (short-term) and

TransZero [arXiv] This repository contains the testing code for the paper "TransZero: Attribute-guided Transformer for Zero-Shot Learning" accepted to

Vision Transformer(ViT) in Tensorflow2 Tensorflow2 implementation of the Vision Transformer(ViT). This repository is for An image is worth 16x16 words

Graph Posterior Network This is the official code repository to the paper Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classifica

SSAT: A Symmetric Semantic-Aware Transformer Network for Makeup Transfer and Removal This is the official pytorch code for SSAT: A Symmetric Semantic-

Convert ONNX model graph to Keras model format.

CTO (Call Tree Overviewer) CTO (Call Tree Overviewer) is an IDA plugin for creating a simple and efficiant function call tree graph. It can also summa

CAPGNN Source code and dataset of the paper "Contrastive Adaptive Propagation Graph Neural Networks forEfficient Graph Learning" Paper URL: https://ar

Official-PyTorch-Implementation-of-TransMEF Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fu

UPT: Unary–Pairwise Transformers This repository contains the official PyTorch implementation for the paper Frederic Z. Zhang, Dylan Campbell and Step

TC-GNN (Running Sparse GNN on Dense Tensor Core on Ampere GPU) Cite this project and paper. @inproceedings{TC-GNN, title={TC-GNN: Accelerating Spars

Open-CyKG: An Open Cyber Threat Intelligence Knowledge Graph Model Description Open-CyKG is a framework that is constructed using an attenti

Decoupled Spatial-Temporal Graph Neural Networks Code for our paper: Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting.

Permutation Invariant Graph Generation via Score-Based Generative Modeling This repo contains the official implementation for the paper Permutation In