Python Graph-transformer Resources

IGMTF The source code and data of the paper "Instance-wise Graph-based Framework for Multivariate Time Series Forecasting". Requirements The framework

VSR-Transformer By Jiezhang Cao, Yawei Li, Kai Zhang, Luc Van Gool This paper proposes a new Transformer for video super-resolution (called VSR-Transf

Anticipative Video Transformer Ranked first in the Action Anticipation task of the CVPR 2021 EPIC-Kitchens Challenge! (entry: AVT-FB-UT) [project page

x-transformers A concise but fully-featured transformer, complete with a set of promising experimental features from various papers. Install $ pip ins

GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition

Zero-Shot Text-to-Speech for Text-Based Insertion in Audio Narration This repo contains only model Implementation of Zero-Shot Text-to-Speech for Text

A Non-Autoregressive Transformer based TTS, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate TTS.

This repository contains an overview of important follow-up works based on the original Vision Transformer (ViT) by Google.

GluonMM is a library of transformer models for computer vision and multi-modality research. It contains reference implementations of widely adopted baseline models and also research work from Amazon Research.

BERT Got a Date: Introducing Transformers to Temporal Tagging Satya Almasian*, Dennis Aumiller*, and Michael Gertz Heidelberg University Contact us vi

Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte

Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context This repository contains the code in both PyTorch and TensorFlow for our paper

English | 简体中文 | 繁體中文 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained mo

ConvE Convolutional 2D Knowledge Graph Embeddings resources. Paper: Convolutional 2D Knowledge Graph Embeddings Used in the paper, but do not use thes

A Pytorch Implementation of the Transformer: Attention Is All You Need Our implementation is largely based on Tensorflow implementation Requirements N

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

Graphlevel-SSL Overview Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Dataset). It is unified framework to co

Tevatron Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models. The toolkit has a modularized

Dynamic Attentive Graph Learning for Image Restoration This repository is for GATIR introduced in the following paper: Chong Mou, Jian Zhang, Zhuoyuan

Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V

SE Aggregation This is the implementation for Rethinking High-order Graph Convolutional Networks. Here we show the codes for citation networks as an e

CrossViT This repository is the official implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification. ArXiv If

Evo-ViT: Slow-Fast Token Evolution for Dynamic Vision Transformer This repository contains the PyTorch code for Evo-ViT. This work proposes a slow-fas

Koi-Koi AI Learning based AI for playing multi-round Koi-Koi hanafuda card games. Platform Python PyTorch PySimpleGUI (for the interface playing vs AI

AAGCN-ACSA EMNLP 2021 Introduction This repository was used in our paper: Beta Distribution Guided Aspect-aware Graph for Aspect Category Sentiment An

Pyan takes one or more Python source files, performs a (rather superficial) static analysis, and constructs a directed graph of the objects in the combined source, and how they define or use each other. The graph can be output for rendering by GraphViz or yEd.

we want to create a repo to illustrate usage of transformers in chinese

A collection of SOTA Image Classification Models in PyTorch

SCT This is the official code for the paper "Tracker Meets Night: A Transformer Enhancer for UAV Tracking" The spatial-channel Transformer (SCT) enhan

DeepPanoContext (DPC) [Project Page (with interactive results)][Paper] DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context G

Transformer in Triton (wip) Implementation of a Transformer, but completely in Triton. I'm completely new to lower-level neural net code, so this repo

3DETR: An End-to-End Transformer Model for 3D Object Detection PyTorch implementation and models for 3DETR. 3DETR (3D DEtection TRansformer) is a simp

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL [Deep Graph Library] and PyTorch.

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

Hierarchical Transformer Memory (HTM) - Pytorch Implementation of Hierarchical Transformer Memory (HTM) for Pytorch. This Deepmind paper proposes a si

CTR-GCN This repo is the official implementation for Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition. The pap

MVGCN MVGCN: a novel multi-view graph convolutional network (MVGCN) framework for link prediction in biomedical bipartite networks. Developer: Fu Hait

Adaptive Graph Convolution for Point Cloud Analysis This repository contains the implementation of AdaptConv for point cloud analysis. Adaptive Graph

Graph2Pix: A Graph-Based Image to Image Translation Framework Installation Install the dependencies in env.yml $ conda env create -f env.yml $ conda a

Single Node Injection Attack against Graph Neural Networks This repository is our Pytorch implementation of our paper: Single Node Injection Attack ag

ANEMONE A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning", CIKM-21 Dependencies python==3.6.1 dgl==

近年来，图计算在搜索、推荐和风控等场景中获得显著的效果，但也面临超大规模异构图训练，与现有的深度学习框架Tensorflow和PyTorch结合等难题。 Galileo（伽利略）是一个图深度学习框架，具备超大规模、易使用、易扩展、高性能、双后端等优点，旨在解决超大规模图算法在工业级场景的落地难题，提

Transformer Captioning This repository contains the code for Transformer-based image captioning. Based on meshed-memory-transformer, we further optimi

Pretrain and Fine-tune a T5 model with Flax on GCP This tutorial details how pretrain and fine-tune a FlaxT5 model from HuggingFace using a TPU VM ava

End-to-end neural table-text understanding models.

✨A Python framework to explore, label, and monitor data for NLP projects

CTRL-C: Camera calibration TRansformer with Line-Classification This repository contains the official code and pretrained models for CTRL-C (Camera ca

nnFormer: Interleaved Transformer for Volumetric Segmentation Code for paper "nnFormer: Interleaved Transformer for Volumetric Segmentation ". Please

Trajectory Transformer Code release for Reinforcement Learning as One Big Sequence Modeling Problem. Installation All python dependencies are in envir

Voxel Transformer This is a reproduced repo of Voxel Transformer for 3D object detection. The code is mainly based on OpenPCDet. Introduction We provi

Adaptive Pyramid Context Network for Semantic Segmentation (APCNet CVPR'2019) Introduction Official implementation of Adaptive Pyramid Context Network

ZSL-KG is a general-purpose zero-shot learning framework with a novel transformer graph convolutional network (TrGCN) to learn class representa

Image-Captioning Keras/Tensorflow Image Captioning application using CNN and Transformer as encoder/decoder. In particulary, the architecture consists

GraphKer Open Source Tool - Cybersecurity Graph Database in Neo4j |G|r|a|p|h|K|e|r| { open source tool for a cybersecurity graph database in neo4j } W

COTREC Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'. Requirements: Python 3.7, Pytorch 1.6.0 Best Hype

MWPToolkit is a PyTorch-based toolkit for Math Word Problem (MWP) solving. It is a comprehensive framework for research purpose that integrates popular MWP benchmark datasets and typical deep learning-based MWP algorithms.

GPT-X using transformer pytorch

Poplar Implementation of Bundle Adjustment using Gaussian Belief Propagation on Graphcore's IPU Implementation of CVPR 2020 paper: Bundle Adjustment o

bert4pytorch 2021年8月27更新： 感谢大家的star，最近有小伙伴反映了一些小的bug，我也注意到了，奈何这个月工作上实在太忙，更新不及时，大约会在9月中旬集中更新一个只需要pip一下就完全可用的版本，然后会新添加一些关键注释。 再增加对抗训练的内容，更新一个完整的finetune

Frustratingly Simple Pretraining Alternatives to Masked Language Modeling This is the official implementation for "Frustratingly Simple Pretraining Al

SGLKT-VisDial Pytorch Implementation for the paper: Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer Gi-Cheon Kang, Junseok P

PaddlePaddle Vision Transformers State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 🤖 PaddlePaddle Visual Transformers (PaddleViT or

Perceiver IO Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs Usage import torch from src.perceiver.

Codebase for training transformers on systematic generalization datasets. The official repository for our EMNLP 2021 paper The Devil is in the Detail:

Megatron (1 and 2) is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA.

Ponder(ing) Transformer Implementation of a Transformer that learns to adapt the number of computational steps it takes depending on the difficulty of

Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation This repository contains the code and models for our paper Tra

GraphGT: Machine Learning Datasets for Graph Generation and Transformation Dataset Website | Paper Installation Using pip To install the core environm

Fast Transformer - Pytorch Implementation of Fast Transformer in Pytorch. This only work as an encoder. Yannic video AI Epiphany Install $ pip install

Differentiable Factor Graph Optimization for Learning Smoothers Overview Status Setup Datasets Training Evaluation Acknowledgements Overview Code rele

SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win

Attention is all you need: A Pytorch Implementation This is a PyTorch implementation of the Transformer model in "Attention is All You Need" (Ashish V

Fast Transformer - Pytorch Implementation of Fast Transformer in Pytorch. This only work as an encoder. Yannic video AI Epiphany Install $ pip install

Ponder(ing) Transformer Implementation of a Transformer that learns to adapt the number of computational steps it takes depending on the difficulty of

Using a predicted aligned error matrix corresponding to an AlphaFold2 model , returns a series of lists of residue indices, where each list corresponds to a set of residues clustering together into a pseudo-rigid domain.

Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Codes for [Preprint] Bag of Tricks for Training Deeper Graph

Demysitifing Local Vision Transformer, arxiv This is the official PyTorch implementation of our paper. We simply replace local self attention by (dyna

Focal Transformer This is the official implementation of our Focal Transformer -- "Focal Self-attention for Local-Global Interactions in Vision Transf

Filtration Curves for Graph Representation This repository provides the code from the KDD'21 paper Filtration Curves for Graph Representation. Depende

MERIT A PyTorch implementation of our IJCAI-21 paper Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning. Depen

Graph-Based Local Trajectory Planner The graph-based local trajectory planner is python-based and comes with open interfaces as well as debug, visuali

SpiderFoot Neo4j Tools Import, visualize, and analyze SpiderFoot OSINT data in Neo4j, a graph database Step 1: Installation NOTE: This installs the sf

transformer-pytorch Transformer model implemented with Pytorch Attention is all you need-[Paper] Architecture Self-Attention self_attention.py class

SIGIR2021-EGLN The implement of paper "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization" Neural graph based Col

Extract knowledge from raw text This repository is a nearly copy-paste of "From Text to Knowledge: The Information Extraction Pipeline" with some cosm

The goal of this project is to create a learning based system that takes an image of a math formula and returns corresponding LaTeX code.

Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv

The DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergence, and present a conditional cross-attention mechanism for fast DETR training. Our approach is motivated by that the cross-attention in DETR relies highly on the content embeddings and that the spatial embeddings make minor contributions, increasing the need for high-quality content embeddings and thus increasing the training difficulty.

R2D2 This is the official code for paper titled "R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Mode

README.md shall be finished soon. WSSGG 0 Overview 1 Installation 1.1 Faster-RCNN 1.2 Language Parser 1.3 GloVe Embeddings 2 Settings 2.1 VG-GT-Graph

Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Official PyTorch implementation of the paper: Improving Graph Neural Net

High-Resolution Transformer for Dense Prediction Introduction This is the official implementation of High-Resolution Transformer (HRT). We present a H

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [Paddle Implementation] Update We have optimized the serial inference p

Vision-Language Transformer and Query Generation for Referring Segmentation Please consider citing our paper in your publications if the project helps

Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp

Code for EmBERT, a transformer model for embodied, language-guided visual task completion.

The tl;dr on a few notable transformer/language model papers + other papers (alignment, memorization, etc).

New State-of-the-Art in Preposition Sense Disambiguation Supervisor: Prof. Dr. Alexander Mehler Alexander Henlein Institutions: Goethe University TTLa

Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson

Graph Convolutional Networks in PyTorch PyTorch implementation of Graph Convolutional Networks (GCNs) for semi-supervised classification [1]. For a hi