1161 Repositories
Python graph-level-representation Libraries
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.
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet)
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-tree Complex Wavelet Representation and Contradict Channel Loss (HDCWNet) (
A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation
A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation
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
This repository contains the code for EMNLP-2021 paper "Word-Level Coreference Resolution"
Word-Level Coreference Resolution This is a repository with the code to reproduce the experiments described in the paper of the same name, which was a
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
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
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 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
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
Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" (NeurIPS'20)
IGNN Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" [paper] [supp] Prepare datasets 1 Download training dataset
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19)
Spatial Attentive Single-Image Deraining with a High Quality Real Rain Dataset (CVPR'19) Tianyu Wang*, Xin Yang*, Ke Xu, Shaozhe Chen, Qiang Zhang, Ry
Benchmark datasets, data loaders, and evaluators for graph machine learning
Overview The Open Graph Benchmark (OGB) is a collection of benchmark datasets, data loaders, and evaluators for graph machine learning. Datasets cover
Implementation of Graph Convolutional Networks in TensorFlow
Graph Convolutional Networks This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of n
official implementation for the paper "Simplifying Graph Convolutional Networks"
Simplifying Graph Convolutional Networks Updates As pointed out by #23, there was a subtle bug in our preprocessing code for the reddit dataset. After
PyTorch Implement for Path Attention Graph Network
SPAGAN in PyTorch This is a PyTorch implementation of the paper "SPAGAN: Shortest Path Graph Attention Network" Prerequisites We prefer to create a ne
Attention over nodes in Graph Neural Networks using PyTorch (NeurIPS 2019)
Intro This repository contains code to generate data and reproduce experiments from our NeurIPS 2019 paper: Boris Knyazev, Graham W. Taylor, Mohamed R
Graph Convolutional Networks for Temporal Action Localization (ICCV2019)
Graph Convolutional Networks for Temporal Action Localization This repo holds the codes and models for the PGCN framework presented on ICCV 2019 Graph
IsoGCN code for ICLR2021
IsoGCN The official implementation of IsoGCN, presented in the ICLR2021 paper Isometric Transformation Invariant and Equivariant Graph Convolutional N
PyTorch implementation of "Simple and Deep Graph Convolutional Networks"
Simple and Deep Graph Convolutional Networks This repository contains a PyTorch implementation of "Simple and Deep Graph Convolutional Networks".(http
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "
[ICML 2020] "When Does Self-Supervision Help Graph Convolutional Networks?" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
When Does Self-Supervision Help Graph Convolutional Networks? PyTorch implementation for When Does Self-Supervision Help Graph Convolutional Networks?
This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
DropEdge: Towards Deep Graph Convolutional Networks on Node Classification This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Con
Repository for benchmarking graph neural networks
Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files
Graph Attention Networks
GAT Graph Attention Networks (Veličković et al., ICLR 2018): https://arxiv.org/abs/1710.10903 GAT layer t-SNE + Attention coefficients on Cora Overvie
PyTorch implementation of residual gated graph ConvNets, ICLR’18
Residual Gated Graph ConvNets April 24, 2018 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbress
Tensorflow Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?"
DeepGCNs: Can GCNs Go as Deep as CNNs? In this work, we present new ways to successfully train very deep GCNs. We borrow concepts from CNNs, mainly re
PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training”
A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”
Fixes your Microphone Level to one specific value.
MicLeveler Fixes your Microphone Level to one specific value. Intention A friend of mine has the problem that some programs are setting his microphone
Markov Chain Composer
Markov Chain Composer Using Markov Chain to represent relationships between words in song lyrics and then generating new lyrics.. ahem interpretive po
Self-Supervised Speech Pre-training and Representation Learning Toolkit.
What's New Sep 2021: We host a challenge in AAAI workshop: The 2nd Self-supervised Learning for Audio and Speech Processing! See SUPERB official site
GraPE is a Rust/Python library for high-performance Graph Processing and Embedding.
GraPE GraPE (Graph Processing and Embedding) is a fast graph processing and embedding library, designed to scale with big graphs and to run on both of
A GOOD REPRESENTATION DETECTS NOISY LABELS
A GOOD REPRESENTATION DETECTS NOISY LABELS This code is a PyTorch implementation of the paper: Prerequisites Python 3.6.9 PyTorch 1.7.1 Torchvision 0.
Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation.
DuoRec Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation. Usage Download datasets fr
This repository implements variational graph auto encoder by Thomas Kipf.
Variational Graph Auto-encoder in Pytorch This repository implements variational graph auto-encoder by Thomas Kipf. For details of the model, refer to
Code for the preprint "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"
This is a repository for the paper of "Well-classified Examples are Underestimated in Classification with Deep Neural Networks" The implementation and
Semi-Supervised Signed Clustering Graph Neural Network (and Implementation of Some Spectral Methods)
SSSNET SSSNET: Semi-Supervised Signed Network Clustering For details, please read our paper. Environment Setup Overview The project has been tested on
A high-level Python library for Quantum Natural Language Processing
lambeq About lambeq is a toolkit for quantum natural language processing (QNLP). Documentation: https://cqcl.github.io/lambeq/ Getting started Prerequ
GarmentNets: Category-Level Pose Estimation for Garments via Canonical Space Shape Completion
GarmentNets This repository contains the source code for the paper GarmentNets: Category-Level Pose Estimation for Garments via Canonical Space Shape
This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022
CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC
Official implementation of "Motif-based Graph Self-Supervised Learning forMolecular Property Prediction"
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Official Pytorch implementation of NeurIPS'21 paper "Motif-based Graph Se
A PoC Corporation Relationship Knowledge Graph System on top of Nebula Graph.
Corp-Rel is a PoC of Corpartion Relationship Knowledge Graph System. It's built on top of the Open Source Graph Database: Nebula Graph with a dataset
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning This repository is the official implementation of CARE.
Code for "Understanding Pooling in Graph Neural Networks"
Select, Reduce, Connect This repository contains the code used for the experiments of: "Understanding Pooling in Graph Neural Networks" Setup Install
Official implementation for Multi-Modal Interaction Graph Convolutional Network for Temporal Language Localization in Videos
Multi-modal Interaction Graph Convolutioal Network for Temporal Language Localization in Videos Official implementation for Multi-Modal Interaction Gr
A brand new hub for Scene Graph Generation methods based on MMdetection (2021). The pipeline of from detection, scene graph generation to downstream tasks (e.g., image cpationing) is supported. Pytorch version implementation of HetH (ECCV 2020) and TopicSG (ICCV 2021) is included.
MMSceneGraph Introduction MMSceneneGraph is an open source code hub for scene graph generation as well as supporting downstream tasks based on the sce
SlideGraph+: Whole Slide Image Level Graphs to Predict HER2 Status in Breast Cancer
SlideGraph+: Whole Slide Image Level Graphs to Predict HER2 Status in Breast Cancer A novel graph neural network (GNN) based model (termed SlideGraph+
Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.
3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
Revitalizing CNN Attention via Transformers in Self-Supervised Visual Representation Learning
A high-level Python library for Quantum Natural Language Processing
lambeq About lambeq is a toolkit for quantum natural language processing (QNLP). Documentation: https://cqcl.github.io/lambeq/ Getting started Prerequ
Code for Understanding Pooling in Graph Neural Networks
Select, Reduce, Connect This repository contains the code used for the experiments of: "Understanding Pooling in Graph Neural Networks" Setup Install
A tool to allow New World players to calculate the best place to put their Attribute Points for their build and level
New World Damage Simulator A tool designed to take a characters base stats including armor and weapons, level, and base damage of their items (slash d
Official PyTorch implementation of "AASIST: Audio Anti-Spoofing using Integrated Spectro-Temporal Graph Attention Networks"
AASIST This repository provides the overall framework for training and evaluating audio anti-spoofing systems proposed in 'AASIST: Audio Anti-Spoofing
The official implementation of the paper, "SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning"
SubTab: Author: Talip Ucar ([email protected]) The official implementation of the paper, SubTab: Subsetting Features of Tabular Data for Self-Supervis
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination
Large Scale Multi-Illuminant (LSMI) Dataset for Developing White Balance Algorithm under Mixed Illumination (ICCV 2021) Dataset License This work is l
Deep Structured Instance Graph for Distilling Object Detectors (ICCV 2021)
DSIG Deep Structured Instance Graph for Distilling Object Detectors Authors: Yixin Chen, Pengguang Chen, Shu Liu, Liwei Wang, Jiaya Jia. [pdf] [slide]
A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation (ICCV 2021)
A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation (ICCV 2021) This repository contains the official implemen
A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search
A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search
Permute Me Softly: Learning Soft Permutations for Graph Representations
Permute Me Softly: Learning Soft Permutations for Graph Representations
Code for the paper Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations (AKBC 2021).
Relation Prediction as an Auxiliary Training Objective for Knowledge Base Completion This repo provides the code for the paper Relation Prediction as
A graph neural network (GNN) model to predict protein-protein interactions (PPI) with no sample features
A graph neural network (GNN) model to predict protein-protein interactions (PPI) with no sample features
A geometric deep learning pipeline for predicting protein interface contacts.
A geometric deep learning pipeline for predicting protein interface contacts.
A framework for evaluating Knowledge Graph Embedding Models in a fine-grained manner.
A framework for evaluating Knowledge Graph Embedding Models in a fine-grained manner.
Float2Binary - A simple python class which finds the binary representation of a floating-point number.
Float2Binary A simple python class which finds the binary representation of a floating-point number. You can find a class in IEEE754.py file with the
The Main Pythonic Version Of Twig Using Nextcord
The Main Pythonic Version Of Twig Using Nextcord
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
Instance-level Image Retrieval using Reranking Transformers
Instance-level Image Retrieval using Reranking Transformers Fuwen Tan, Jiangbo Yuan, Vicente Ordonez, ICCV 2021. Abstract Instance-level image retriev
Code for CodeT5: a new code-aware pre-trained encoder-decoder model.
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation This is the official PyTorch implementation
DGCNN - Dynamic Graph CNN for Learning on Point Clouds
DGCNN is the author's re-implementation of Dynamic Graph CNN, which achieves state-of-the-art performance on point-cloud-related high-level tasks including category classification, semantic segmentation and part segmentation.
3D-Transformer: Molecular Representation with Transformer in 3D Space
3D-Transformer: Molecular Representation with Transformer in 3D Space
ICLR 2021: Pre-Training for Context Representation in Conversational Semantic Parsing
SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing This repository contains code for the ICLR 2021 paper "SCoRE: Pre-Tr
A test Django application with production-level docker setup
DockerApp A test Django application with production-level docker setup. Blog: https://medium.com/@siddharth.sahu/the-near-perfect-dockerfile-for-djang
GRF: Learning a General Radiance Field for 3D Representation and Rendering
GRF: Learning a General Radiance Field for 3D Representation and Rendering [Paper] [Video] GRF: Learning a General Radiance Field for 3D Representatio
First and foremost, we want dbt documentation to retain a DRY principle. Every time we repeat ourselves, we waste our time. Second, we want to understand column level lineage and automate impact analysis.
dbt-osmosis First and foremost, we want dbt documentation to retain a DRY principle. Every time we repeat ourselves, we waste our time. Second, we wan
Pytorch implementation of CVPR2020 paper “VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation”
VectorNet Re-implementation This is the unofficial pytorch implementation of CVPR2020 paper "VectorNet: Encoding HD Maps and Agent Dynamics from Vecto
Control System Packer is a lightweight, low-level program to transform energy equations into the compact libraries for control systems.
Control System Packer is a lightweight, low-level program to transform energy equations into the compact libraries for control systems. Packer supports Python 🐍 , C 💻 and C++ 💻 libraries.
The source code and data of the paper "Instance-wise Graph-based Framework for Multivariate Time Series Forecasting".
IGMTF The source code and data of the paper "Instance-wise Graph-based Framework for Multivariate Time Series Forecasting". Requirements The framework
A self-supervised 3D representation learning framework named viewpoint bottleneck.
Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In
GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming
Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification.
A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte
Convolutional 2D Knowledge Graph Embeddings resources
ConvE Convolutional 2D Knowledge Graph Embeddings resources. Paper: Convolutional 2D Knowledge Graph Embeddings Used in the paper, but do not use thes
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining
The PASS dataset: pretrained models and how to get the data - PASS: Pictures without humAns for Self-Supervised Pretraining
Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Datset)
Graphlevel-SSL Overview Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Dataset). It is unified framework to co
A collection of repositories used to realise various end-to-end high-level synthesis (HLS) flows centering around the CIRCT project.
circt-hls What is this?: A collection of repositories used to realise various end-to-end high-level synthesis (HLS) flows centering around the CIRCT p
Dynamic Attentive Graph Learning for Image Restoration, ICCV2021 [PyTorch Code]
Dynamic Attentive Graph Learning for Image Restoration This repository is for GATIR introduced in the following paper: Chong Mou, Jian Zhang, Zhuoyuan
High level network definitions with pre-trained weights in TensorFlow
TensorNets High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 = TF = 1.4.0). Guiding principles Applicability.
Library for fast text representation and classification.
fastText fastText is a library for efficient learning of word representations and sentence classification. Table of contents Resources Models Suppleme
Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
Human-Level Control through Deep Reinforcement Learning Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning. This imp
Official DGL implementation of "Rethinking High-order Graph Convolutional Networks"
SE Aggregation This is the implementation for Rethinking High-order Graph Convolutional Networks. Here we show the codes for citation networks as an e