963 Repositories
Python knowledge-graph-embeddings Libraries
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)
A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G
Count the frequency of letters or words in a text file and show a graph.
Word Counter By EBUS Coding Club Count the frequency of letters or words in a text file and show a graph. Requirements Python 3.9 or higher matplotlib
Official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Imbalance Classification"
DPGNN This repository is an official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Im
Language Models for the legal domain in Spanish done @ BSC-TEMU within the "Plan de las Tecnologías del Lenguaje" (Plan-TL).
Spanish legal domain Language Model ⚖️ This repository contains the page for two main resources for the Spanish legal domain: A RoBERTa model: https:/
Dynamic Graph Event Detection
DyGED Dynamic Graph Event Detection Get Started pip install -r requirements.txt TODO Paper link to arxiv, and how to cite. Twitter Weather dataset tra
Harmonic Memory Networks for Graph Completion
HMemNetworks Code and documentation for Harmonic Memory Networks, a series of models for compositionally assembling representations of graph elements
A Broader Picture of Random-walk Based Graph Embedding
Random-walk Embedding Framework This repository is a reference implementation of the random-walk embedding framework as described in the paper: A Broa
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k
IEEE Winter Conference on Applications of Computer Vision 2022 Accepted
SSKT(Accepted WACV2022) Concept map Dataset Image dataset CIFAR10 (torchvision) CIFAR100 (torchvision) STL10 (torchvision) Pascal VOC (torchvision) Im
A novel pipeline framework for multi-hop complex KGQA task. About the paper title: Improving Multi-hop Embedded Knowledge Graph Question Answering by Introducing Relational Chain Reasoning
Rce-KGQA A novel pipeline framework for multi-hop complex KGQA task. This framework mainly contains two modules, answering_filtering_module and relati
Wanli Li and Tieyun Qian: Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction, IJCNN 2021
MRefG Wanli Li and Tieyun Qian: "Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction", IJCNN 2021 1. Requirements To reproduc
Neo4j Movies Example application with Flask backend using the neo4j-python-driver
Neo4j Movies Application: Quick Start This example application demonstrates how easy it is to get started with Neo4j in Python. It is a very simple we
This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021.
MCGC Description This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021. Datasets Results ACM DBLP IMDB Amazon photos Amazon co
Django database backed celery periodic task scheduler with support for task dependency graph
Djag Scheduler (Dj)ango Task D(AG) (Scheduler) Overview Djag scheduler associates scheduling information with celery tasks The task schedule is persis
Created as part of CS50 AI's coursework. This AI makes use of knowledge entailment to calculate the best probabilities to win Minesweeper.
Minesweeper-AI Created as part of CS50 AI's coursework. This AI makes use of knowledge entailment to calculate the best probabilities to win Minesweep
Spatial-Temporal Transformer for Dynamic Scene Graph Generation, ICCV2021
Spatial-Temporal Transformer for Dynamic Scene Graph Generation Pytorch Implementation of our paper Spatial-Temporal Transformer for Dynamic Scene Gra
Self-supervised learning on Graph Representation Learning (node-level task)
graph_SSL Self-supervised learning on Graph Representation Learning (node-level task) How to run the code To run GRACE, sh run_GRACE.sh To run GCA, sh
Key information extraction from invoice document with Graph Convolution Network
Key Information Extraction from Scanned Invoices Key information extraction from invoice document with Graph Convolution Network Related blog post fro
Blog focused on skills enhancement and knowledge sharing. Tech Stack's: Vue.js, Django and Django-Ninja
Blog focused on skills enhancement and knowledge sharing. Tech Stack's: Vue.js, Django and Django-Ninja
This is the code of NeurIPS'21 paper "Towards Enabling Meta-Learning from Target Models".
ST This is the code of NeurIPS 2021 paper "Towards Enabling Meta-Learning from Target Models". If you use any content of this repo for your work, plea
Meta graph convolutional neural network-assisted resilient swarm communications
Resilient UAV Swarm Communications with Graph Convolutional Neural Network This repository contains the source codes of Resilient UAV Swarm Communicat
Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge
Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge This is an implementation of the paper,
Bootstrapped Unsupervised Sentence Representation Learning (ACL 2021)
Install first pip3 install -e . Training python3 training/unsupervised_tuning.py python3 training/supervised_tuning.py python3 training/multilingual_
Code for reproducing our paper: LMSOC: An Approach for Socially Sensitive Pretraining
LMSOC: An Approach for Socially Sensitive Pretraining Code for reproducing the paper LMSOC: An Approach for Socially Sensitive Pretraining to appear a
Knowledge Oriented Programming Language
KoPL: 面向知识的推理问答编程语言 安装 | 快速开始 | 文档 KoPL全称 Knowledge oriented Programing Language, 是一个为复杂推理问答而设计的编程语言。我们可以将自然语言问题表示为由基本函数组合而成的KoPL程序,程序运行的结果就是问题的答案。目前,
Code and datasets for the paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction"
KnowPrompt Code and datasets for our paper "KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction" Requireme
A Word Level Transformer layer based on PyTorch and 🤗 Transformers.
Transformer Embedder A Word Level Transformer layer based on PyTorch and 🤗 Transformers. How to use Install the library from PyPI: pip install transf
Code for Findings at EMNLP 2021 paper: "Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning"
Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning This repo is for Findings at EMNLP 2021 paper: Learn Cont
Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo.
stock-graph-python Simple CLI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your
Retentioneering: product analytics, data-driven customer journey map optimization, marketing analytics, web analytics, transaction analytics, graph visualization, and behavioral segmentation with customer segments in Python.
What is Retentioneering? Retentioneering is a Python framework and library to assist product analysts and marketing analysts as it makes it easier to
PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks
Code for the paper "PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks" (ICPR 2020)
Python Implementation of algorithms in Graph Mining, e.g., Recommendation, Collaborative Filtering, Community Detection, Spectral Clustering, Modularity Maximization, co-authorship networks.
Graph Mining Author: Jiayi Chen Time: April 2021 Implemented Algorithms: Network: Scrabing Data, Network Construbtion and Network Measurement (e.g., P
Watson Natural Language Understanding and Knowledge Studio
Material de demonstração dos serviços: Watson Natural Language Understanding e Knowledge Studio Visão Geral: https://www.ibm.com/br-pt/cloud/watson-na
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Vector AI — A platform for building vector based applications. Encode, query and analyse data using vectors.
Vector AI is a framework designed to make the process of building production grade vector based applications as quickly and easily as possible. Create
image scene graph generation benchmark
Scene Graph Benchmark in PyTorch 1.7 This project is based on maskrcnn-benchmark Highlights Upgrad to pytorch 1.7 Multi-GPU training and inference Bat
EMNLP'2021: SimCSE: Simple Contrastive Learning of Sentence Embeddings
SimCSE: Simple Contrastive Learning of Sentence Embeddings This repository contains the code and pre-trained models for our paper SimCSE: Simple Contr
Source code for the paper "PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction" in ACL2021
PLOME:Pre-training with Misspelled Knowledge for Chinese Spelling Correction (ACL2021) This repository provides the code and data of the work in ACL20
MutualGuide is a compact object detector specially designed for embedded devices
Introduction MutualGuide is a compact object detector specially designed for embedded devices. Comparing to existing detectors, this repo contains two
Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge
Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge This is an implementation of the paper,
This repository contains the code for the paper in EMNLP 2021: "HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression".
HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression This repository contains the code for the paper in EM
PyTorch implementation of "Dataset Knowledge Transfer for Class-Incremental Learning Without Memory" (WACV2022)
Dataset Knowledge Transfer for Class-Incremental Learning Without Memory [Paper] [Slides] Summary Introduction Installation Reproducing results Citati
Temporal Knowledge Graph Reasoning Triggered by Memories
MTDM Temporal Knowledge Graph Reasoning Triggered by Memories To alleviate the time dependence, we propose a memory-triggered decision-making (MTDM) n
Membership Inference Attack against Graph Neural Networks
MIA GNN Project Starter If you meet the version mismatch error for Lasagne library, please use following command to upgrade Lasagne library. pip insta
Official PyTorch implementation of "Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient".
Edge Rewiring Goes Neural: Boosting Network Resilience via Policy Gradient This repository is the official PyTorch implementation of "Edge Rewiring Go
A graph-to-sequence model for one-step retrosynthesis and reaction outcome prediction.
Graph2SMILES A graph-to-sequence model for one-step retrosynthesis and reaction outcome prediction. 1. Environmental setup System requirements Ubuntu:
This is the official code of L2G, Unrolling and Recurrent Unrolling in Learning to Learn Graph Topologies.
Learning to Learn Graph Topologies This is the official code of L2G, Unrolling and Recurrent Unrolling in Learning to Learn Graph Topologies. Requirem
VLG-Net: Video-Language Graph Matching Networks for Video Grounding
VLG-Net: Video-Language Graph Matching Networks for Video Grounding Introduction Official repository for VLG-Net: Video-Language Graph Matching Networ
Learning Fair Representations for Recommendation: A Graph-based Perspective, WWW2021
FairGo WWW2021 Learning Fair Representations for Recommendation: A Graph-based Perspective As a key application of artificial intelligence, recommende
A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (WSDM 2021)
FairGNN A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (
Code for ICML2019 Paper "Compositional Invariance Constraints for Graph Embeddings"
Dependencies NOTE: This code has been updated, if you were using this repo earlier and experienced issues that was due to an outaded codebase. Please
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation This repository contains the source code of the SIGIR 2019 paper "Reinforcement
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Accuracy-Diversity Trade-off in Recommender Systems via Graph Convolutions
Accuracy-Diversity Trade-off in Recommender Systems via Graph Convolutions This repository contains the code of the paper "Accuracy-Diversity Trade-of
The official implementation of "DGCN: Diversified Recommendation with Graph Convolutional Networks" (WWW '21)
DGCN This is the official implementation of our WWW'21 paper: Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li, DGCN: Diversified Recommendation wi
The implementation of the submitted paper "Deep Multi-Behaviors Graph Network for Voucher Redemption Rate Prediction" in SIGKDD 2021 Applied Data Science Track.
DMBGN: Deep Multi-Behaviors Graph Networks for Voucher Redemption Rate Prediction The implementation of the accepted paper "Deep Multi-Behaviors Graph
This is our implementation of GHCF: Graph Heterogeneous Collaborative Filtering (AAAI 2021)
GHCF This is our implementation of the paper: Chong Chen, Weizhi Ma, Min Zhang, Zhaowei Wang, Xiuqiang He, Chenyang Wang, Yiqun Liu and Shaoping Ma. 2
Code for my ORSUM, ACM RecSys 2020, HeroGRAPH: A Heterogeneous Graph Framework for Multi-Target Cross-Domain Recommendation
HeroGRAPH Code for my ORSUM @ RecSys 2020, HeroGRAPH: A Heterogeneous Graph Framework for Multi-Target Cross-Domain Recommendation Paper, workshop pro
Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks
Bi-TGCF Tensorflow Implementation of BiTGCF: Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks. in CIKM20
Hierarchical Fashion Graph Network for Personalized Outfit Recommendation, SIGIR 2020
hierarchical_fashion_graph_network This is our Tensorflow implementation for the paper: Xingchen Li, Xiang Wang, Xiangnan He, Long Chen, Jun Xiao, and
Bundle Graph Convolutional Network
Bundle Graph Convolutional Network This is our Pytorch implementation for the paper: Jianxin Chang, Chen Gao, Xiangnan He, Depeng Jin and Yong Li. Bun
Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'.
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
[ICDMW 2020] Code and dataset for "DGTN: Dual-channel Graph Transition Network for Session-based Recommendation"
DGTN: Dual-channel Graph Transition Network for Session-based Recommendation This repository contains PyTorch Implementation of ICDMW 2020 (NeuRec @ I
Incorporating User Micro-behaviors and Item Knowledge 59 60 3 into Multi-task Learning for Session-based Recommendation
MKM-SR Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation Paper data and code This is the
The source code for "Global Context Enhanced Graph Neural Network for Session-based Recommendation".
GCE-GNN Code This is the source code for SIGIR 2020 Paper: Global Context Enhanced Graph Neural Networks for Session-based Recommendation. Requirement
Handling Information Loss of Graph Neural Networks for Session-based Recommendation
LESSR A PyTorch implementation of LESSR (Lossless Edge-order preserving aggregation and Shortcut graph attention for Session-based Recommendation) fro
Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction
MGNN-SPred This is our Tensorflow implementation for the paper: WenWang,Wei Zhang, Shukai Liu, Qi Liu, Bo Zhang, Leyu Lin, and Hongyuan Zha. 2020. Bey
This is our Tensorflow implementation for "Graph-based Embedding Smoothing for Sequential Recommendation" (GES) (TKDE, 2021).
Graph-based Embedding Smoothing (GES) This is our Tensorflow implementation for the paper: Tianyu Zhu, Leilei Sun, and Guoqing Chen. "Graph-based Embe
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer
Introduction This is the repository of our accepted CIKM 2021 paper "Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Trans
RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation
RetaGNN: Relational Temporal Attentive Graph Neural Networks for Holistic Sequential Recommendation Pytorch based implemention of Relational Temporal
Group-Buying Recommendation for Social E-Commerce
Group-Buying Recommendation for Social E-Commerce This is the official implementation of the paper Group-Buying Recommendation for Social E-Commerce (
Knowledge-aware Coupled Graph Neural Network for Social Recommendation
KCGN AAAI-2021 《Knowledge-aware Coupled Graph Neural Network for Social Recommendation》 Environments python 3.8 pytorch-1.6 DGL 0.5.3 (https://github.
Graph Neural Network based Social Recommendation Model. SIGIR2019.
Basic Information: This code is released for the papers: Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang and Meng Wang. A Neural Influence Dif
Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks
SR-HGNN ICDM-2020 《Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks》 Environments python 3.8 pytorch-1.6 DGL 0.5.
A tensorflow implementation of the RecoGCN model in a CIKM'19 paper, titled with "Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation".
This repo contains a tensorflow implementation of RecoGCN and the experiment dataset Running the RecoGCN model python train.py Example training outp
Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems
DANSER-WWW-19 This repository holds the codes for Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recom
Detecting Beneficial Feature Interactions for Recommender Systems, AAAI 2021
Detecting Beneficial Feature Interactions for Recommender Systems (L0-SIGN) This is our implementation for the paper: Su, Y., Zhang, R., Erfani, S., &
Price-aware Recommendation with Graph Convolutional Networks,
PUP This is the official implementation of our ICDE'20 paper: Yu Zheng, Chen Gao, Xiangnan He, Yong Li, Depeng Jin, Price-aware Recommendation with Gr
Self-supervised Graph Learning for Recommendation
SGL This is our Tensorflow implementation for our SIGIR 2021 paper: Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian,and Xing
An index of recommendation algorithms that are based on Graph Neural Networks.
An index of recommendation algorithms that are based on Graph Neural Networks.
Residual2Vec: Debiasing graph embedding using random graphs
Residual2Vec: Debiasing graph embedding using random graphs This repository contains the code for S. Kojaku, J. Yoon, I. Constantino, and Y.-Y. Ahn, R
This folder contains the implementation of the multi-relational attribute propagation algorithm.
MrAP This folder contains the implementation of the multi-relational attribute propagation algorithm. It requires the package pytorch-scatter. Please
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations)
Graph Neural Networks with Learnable Structural and Positional Representations Source code for the paper "Graph Neural Networks with Learnable Structu
Code for “ACE-HGNN: Adaptive Curvature ExplorationHyperbolic Graph Neural Network”
ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network This repository is the implementation of ACE-HGNN in PyTorch. Environment pyt
Data and code for ICCV 2021 paper Distant Supervision for Scene Graph Generation.
Distant Supervision for Scene Graph Generation Data and code for ICCV 2021 paper Distant Supervision for Scene Graph Generation. Introduction The pape
Weakly-supervised Text Classification Based on Keyword Graph
Weakly-supervised Text Classification Based on Keyword Graph How to run? Download data Our dataset follows previous works. For long texts, we follow C
novel deep learning research works with PaddlePaddle
Research 发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa
Asymmetric metric learning for knowledge transfer
Asymmetric metric learning This is the official code that enables the reproduction of the results from our paper: Asymmetric metric learning for knowl
Hacking github graph with a easy python script
Hacking-Github-Graph Hacking github graph with a easy python script Requirements git latest version installed. A text editor (eg: vs code, sublime tex
Code for the ICME 2021 paper "Exploring Driving-Aware Salient Object Detection via Knowledge Transfer"
TSOD Code for the ICME 2021 paper "Exploring Driving-Aware Salient Object Detection via Knowledge Transfer" Usage For training, open train_test, run p
Source Code for our paper: Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Network
KaGRMN-DSG_ABSA This repository contains the PyTorch source Code for our paper: Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated
Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021.
Semi-Supervised Graph Prototypical Networks for Hyperspectral Image Classification, IGARSS, 2021. Bobo Xi, Jiaojiao Li, Yunsong Li and Qian Du. Code f
KUIZ is a web application quiz where you can create/take a quiz for learning and sharing knowledge from various subjects, questions and answers.
KUIZ KUIZ is a web application quiz where you can create/take a quiz for learning and sharing knowledge from various subjects, questions and answers.
A D3.js plugin that produces flame graphs from hierarchical data.
d3-flame-graph A D3.js plugin that produces flame graphs from hierarchical data. If you don't know what flame graphs are, check Brendan Gregg's post.
The official implementation of CVPR 2021 Paper: Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation.
Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation This repository is the official implementation of CVPR 2021 paper:
The official PyTorch implementation for the paper "sMGC: A Complex-Valued Graph Convolutional Network via Magnetic Laplacian for Directed Graphs".
Magnetic Graph Convolutional Networks About The official PyTorch implementation for the paper sMGC: A Complex-Valued Graph Convolutional Network via M
SoGCN: Second-Order Graph Convolutional Networks
SoGCN: Second-Order Graph Convolutional Networks This is the authors' implementation of paper "SoGCN: Second-Order Graph Convolutional Networks" in Py
Using contrastive learning and OpenAI's CLIP to find good embeddings for images with lossy transformations
Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr
novel deep learning research works with PaddlePaddle
Research 发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa
Implementation of paper "Graph Condensation for Graph Neural Networks"
GCond A PyTorch implementation of paper "Graph Condensation for Graph Neural Networks" Code will be released soon. Stay tuned :) Abstract We propose a