Python Knowledge-graph-for-recommendation Resources

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

DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari

SegDistill: Toolbox for Knowledge Distillation on Semantic Segmentation Networks This repo contains the supported code and configuration files for Seg

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-detection-tg-bot A Recommendation System For Diabetes Detection And Treatment Данная система помогает определить наличие или отсутствие сахар

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

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

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

PAML PyTorch implementation of the paper: "Preference-Adaptive Meta-Learning for Cold-Start Recommendation", IJCAI, 2021. (Continuously updating ) Int

GNet-pose Project Page: http://guanghan.info/projects/guided-fractal/ UPDATE 9/27/2018: Prototxts and model that achieved 93.9Pck on LSP dataset. http

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

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

Open-KG-canonicalization The software associated with a paper accepted at EMNLP 2021 titled "Open Knowledge Graphs Canonicalization using Variational

High performance distributed framework for training deep learning recommendation models based on PyTorch.

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

Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA

Robust and Accurate Object Detection via Self-Knowledge Distillation paper:https://arxiv.org/abs/2111.07239 Environments Python 3.7 Cuda 10.1 Prepare

TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations Requirements python 3.6 torch 1.9 numpy 1.19 Quick Start The experimen

Zero-Shot Learning in Named Entity Recognition with Common Sense Knowledge Associated code for the paper Zero-Shot Learning in Named Entity Recognitio

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?

Knowledge Base Completion Meets Transfer Learning This code accompanies the paper Knowledge Base Completion Meets Transfer Learning published at EMNLP

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

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

recommendersystem Recommendation System to recommend top books from the dataset Introduction The recom.py is the main program code. The dataset is als

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

GOAT A paper using optimal transport to solve the graph matching problem. https://arxiv.org/abs/2111.05366 Repo structure .github: Files specifying ho

isvd Official implementation of NeurIPS'21: Implicit SVD for Graph Representation Learning If you find this code useful, you may cite us as: @inprocee

Climate Modeling with Neural Diffusion Equation Introduction This is the repository of our accepted ICDM 2021 paper "Climate Modeling with Neural Diff

This is a sport analytics project that combines the knowledge of Object Oriented Programming (OOP) and Webscraping, the weekly scraping of the English Premier league table is carried out to assess the performance of each club from the beginning of the season to the end.

Trans-Net Code for (Visual Boundary Knowledge Translation for Foreground Segmentation, AAAI2021). [https://ojs.aaai.org/index.php/AAAI/article/view/16

SGTL - Spectral Graph Theory Library SGTL is a python library of spectral graph theory methods. The library is still very new and so there are many fe

ICS-Visualizer is an interactive Industrial Control Systems (ICS) network graph that contains up-to-date ICS metadata (Name, company, port, user manua

Overview Metrinome is an all-purpose tool for working with code complexity metrics. It can be used as both a REPL and API, and includes: Converters to

Py2neo Py2neo is a client library and toolkit for working with Neo4j from within Python applications. The library supports both Bolt and HTTP and prov

Fair Recommendation in Two-Sided Platforms

Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks This is our Pytorch implementation for the paper: Zirui Zhu, Chen Gao, Xu C

Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods Introduction Graph Neural Networks (GNNs) have demonstrated

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

Homepage | Paper | Datasets | Leaderboard | Documentation Graph Robustness Benchmark (GRB) provides scalable, unified, modular, and reproducible evalu

Contrastive Learning for Cold-start Recommendation This is our Pytorch implementation for the paper: Yinwei Wei, Xiang Wang, Qi Li, Liqiang Nie, Yan L

Entity-Based Knowledge Conflicts in Question Answering Run Instructions | Paper | Citation | License This repository provides the Substitution Framewo

Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp

Instance-conditional Knowledge Distillation for Object Detection This is a MegEngine implementation of the paper "Instance-conditional Knowledge Disti

GDN A tensorflow=1.13 implementation of Deconvolutional Networks on Graph Data (NeurIPS 2021) Abstract In this paper, we consider an inverse problem i

SGMNet Implementation PyTorch implementation of SGMNet for ICCV'21 paper "Learning to Match Features with Seeded Graph Matching Network", by Hongkai C

Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification

Towards Continual Knowledge Learning of Language Models This is the official github repository for Towards Continual Knowledge Learning of Language Mo

Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods This is the code repository to accompany the EMNLP 2021 paper on ad

Geometric Graphs Generate knowledge graphs with interesting geometries, like lattices. Works on Python 3.9+ because it uses cool new features. Get out

CaGCN This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration". Paper L

Project Name: Fasion Recommendation System for Ecommerce A Deep learning based streamlit web app which can recommened you various types of fasion prod

Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp

ADGCL : Adversarial Graph Augmentation to Improve Graph Contrastive Learning Introduction This repo contains the Pytorch [1] implementation of Adversa

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro

Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback This is our Pytorch implementation for the paper: Yinwei Wei,

RHGN Source code for CIKM 2021 paper for Relation-aware Heterogeneous Graph for User Profiling Dependencies torch==1.6.0 torchvision==0.7.0 dgl==0.7.1

UV-matrix-decompostion-with-kfold UV matrix decompostion using movielens dataset upload the 'ratings.dat' file install the following python libraries

Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods Introduction Graph Neural Networks (GNNs) have demonstrated

Edge Independent Graph Models Code for the paper: "On the Power of Edge Independent Graph Models" Sudhanshu Chanpuriya, Cameron Musco, Konstantinos So

IGCN : Image-to-graph convolutional network IGCN is a learning framework for 2D/3D deformable model registration and alignment, and shape reconstructi

LEAR The implementation our EMNLP 2021 paper "Enhanced Language Representation with Label Knowledge for Span Extraction". **The code is in the "master

RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining Our code is based on Learning Attention-based Embed

简体中文 | English PaddleClas 简介 飞桨图像识别套件PaddleClas是飞桨为工业界和学术界所准备的一个图像识别任务的工具集，助力使用者训练出更好的视觉模型和应用落地。 近期更新 2021.11.1 发布PP-ShiTu技术报告，新增饮料识别demo 2021.10.23 发

Data and Code for paper Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graph is available f

MIRCO PyTorch implementation for paper: Latent Structures Mining with Contrastive Modality Fusion for Multimedia Recommendation Dependencies Python 3.

DSP: Trajectory Prediction with Graph-based Dual-scale Context Fusion Introduction This is the project page of the paper Lu Zhang, Peiliang Li, Jing C

Diverse Motion Stylization (Official) This is the official Pytorch implementation of this paper. Diverse Motion Stylization for Multiple Style Domains

DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021] Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng

A large-scale database for graph representation learning

LOCKER This is the pytorch implementation of this paper: Locally Constrained Self-Attentive Sequential Recommendation. Zhankui He, Handong Zhao, Zhe L

Enhancing Knowledge Tracing via Adversarial Training This repository contains source code for the paper "Enhancing Knowledge Tracing via Adversarial T

UltraGCN This is our Pytorch implementation for our CIKM 2021 paper: Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He. UltraGCN: A

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Abstract Graph Neural Networks (GNNs) are widely used on a

Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach This is the implementation of traffic prediction code in DTMP based on PyTo

stock-graph-python Simple GUI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your

Spotify-Song-Recommendation-Program Made by Esra Nur Özüm Written in Python The aim of this project was to build a recommendation system that recommen

CKDN The official implementation of the ICCV2021 paper "Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment" O

Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric

Ansible Playbook Grapher ansible-playbook-grapher is a command line tool to create a graph representing your Ansible playbook plays, tasks and roles.

GRecX A Fair Benchmark for GNN-based Recommendation Preliminary Comparison DiffNet-Yelp dataset (featureless) Algo nDCG@5 nDCG@10 nDCG@15 MF 0.158707

Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering

Heterogeneous Temporal Graph Neural Network This repository contains the datasets and source code of HTGNN. run_mag.ipynb is the training and testing

ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs This is the code of paper ConE: Cone Embeddings for Multi-Hop Reasoning over Knowl

Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro

MosaicKD Code for NeurIPS-21 paper "Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data" 1. Motivation Natural images share common l

BMVC 2021 BI-GConv: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation Necassary Dependencies: PyTorch 1.2.0 Python 3.

VACA Code repository for the paper "VACA: Designing Variational Graph Autoencoders for Interventional and Counterfactual Queries (arXiv)". The impleme

Rot-Pro : Modeling Transitivity by Projection in Knowledge Graph Embedding This repository contains the source code for the Rot-Pro model, presented a

Node Dependent Local Smoothing for Scalable Graph Learning Requirements Environments: Xeon Gold 5120 (CPU), 384GB(RAM), TITAN RTX (GPU), Ubuntu 16.04

SparseCard Code for approximate graph reduction techniques for cardinality-based DSFM, from paper "Approximate Decomposable Submodular Function Minimi

Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs SMORE is a a versatile framework that scales multi-hop query emb