149 Open source projects that are alternatives of or similar to DiGCL

Code and resources on scalable and efficient Graph Neural Networks

[NeurIPS 2021 Spotlight] Aligning Pretraining for Detection via Object-Level Contrastive Learning

Code of the NeurIPS 2021 paper: Language and Visual Entity Relationship Graph for Agent Navigation

A curated list of awesome graph & self-supervised-learning-based recommendation.

source code for signed graph attention networks (ICANN2019) & SDGNN (AAAI2021)

Deprecated: Use the @encapsule/arccore package that includes the graph library

PyTorch Implementation on Paper [CVPR2021]Distilling Audio-Visual Knowledge by Compositional Contrastive Learning

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

[ICLR 2021] How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision

Code snippets and solutions for the Introduction to Deep Learning and Neural Networks Course hosted in educative.io

A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in The International Workshop on Self-Supervised Learning for the Web (SSL'21) @ the Web Conference 2021 (WWW'21).

Context-Aware Visual Compatibility Prediction (https://arxiv.org/abs/1902.03646)

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning (authors' MXNet implementation for the TACL19 paper)

Generalized Deep Metric Learning.

S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

Official PyTorch implementation of Contrastive Learning of Musical Representations

Code for the CHAMPS Predicting Molecular Properties Kaggle competition

🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba 来自阿里巴巴的一站式大规模图计算系统 图分析 图查询 图机器学习

Visualization tool for Graph Neural Networks

Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations. [NeurIPS 2021]

Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.

Object-aware Contrastive Learning for Debiased Scene Representation (NeurIPS 2021)

This repository contains the code implementation used in the paper Temporally Coherent Embeddings for Self-Supervised Video Representation Learning (TCE).

Subgraph Neural Networks (NeurIPS 2020)

Implementation for "3D human pose, shape and texture from low-resolution images and videos", TPAMI 2021

Official implementation of CATs

Awesome Graph Self-Supervised Learning

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Tutorials for Machine Learning on Graphs

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

Pytorch differentiable molecular dynamics

Code and data for ECML-PKDD paper "Social Influence Attentive Neural Network for Friend-Enhanced Recommendation"

Locally Private Graph Neural Networks (ACM CCS 2021)

Fast Image Retrieval (FIRe) is an open source project to promote image retrieval research. It implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.

Implementation of "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" in PyTorch

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

A spherical CNN for weather forecasting

Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks

Code for the paper "DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors".

GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification

Message Passing Neural Networks for Simplicial and Cell Complexes

Material for the EPFL master course "A Network Tour of Data Science", edition 2019.

[WACV'22] Code repository for the paper "Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting", https://arxiv.org/abs/2106.10137.

Reimplementation of Graph Embedding methods by Pytorch.

Implementation of the paper "Certifiable Robustness and Robust Training for Graph Convolutional Networks".

Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

Demo of RouteNet in ACM SIGCOMM'19

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

official implemntation for "Contrastive Learning with Stronger Augmentations"

PyTorch implementation of the InfoNCE loss for self-supervised learning.

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

Parametric Contrastive Learning (ICCV2021)

Implements the ideas presented in https://arxiv.org/pdf/2004.11362v1.pdf by Khosla et al.

An index of recommendation algorithms that are based on Graph Neural Networks.

CVC: Contrastive Learning for Non-parallel Voice Conversion (INTERSPEECH 2021, in PyTorch)

Summary of social recommendation papers and codes

Disentagnled Graph Collaborative Filtering, SIGIR2020

Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

AAAI'21: Data Augmentation for Graph Neural Networks