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

Awesome Graph Self-Supervised Learning

Fast Inference of Networks from Directed Regulations

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

Dart implementation of a directed graph. Provides algorithms for sorting vertices, retrieving a topological ordering or detecting cycles.

Tutorials for Machine Learning on Graphs

StellarGraph - Machine Learning on Graphs

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

Graph Neural Network Library for PyTorch

Pytorch differentiable molecular dynamics

Python package built to ease deep learning on graph, on top of existing DL frameworks.

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

Implementation of Directional Graph Networks in PyTorch and DGL

Locally Private Graph Neural Networks (ACM CCS 2021)

Implementation of "Overlapping Community Detection with Graph Neural Networks"

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.

Graph-based Deep Q Network for Web Navigation

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

Combining relational context and relational paths for knowledge graph completion

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

A new codebase for Group Activity Recognition. It contains codes for ICCV 2021 paper: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition and some other methods.

A spherical CNN for weather forecasting

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

Probabilistic Type Inference using Graph Neural Networks

Combining relational context and relational paths for knowledge graph completion

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

Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"

GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification

Codes for "Bridging the Gap Between Spectral and Spatial Domains in Graph Neural Networks" paper

Message Passing Neural Networks for Simplicial and Cell Complexes

Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

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

[IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"

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

A reading list for deep graph learning acceleration.

Visualization tool for Graph Neural Networks

Reimplementation of Graph Embedding methods by Pytorch.

Summary of social recommendation papers and codes

odr.chalmers.se/handle/20.500.12380/256629?locale=en

Papers about explainability of GNNs

Demo of RouteNet in ACM SIGCOMM'19

This is a paper list about Resource Allocation in Network Functions Virtualization (NFV) and Software-Defined Networking (SDN).

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

Smart Contract Vulnerability Detection Using Graph Neural Networks (IJCAI-20 Accepted)

official implemntation for "Contrastive Learning with Stronger Augmentations"

TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding (code & data)

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

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

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

Representing Long-Range Context for Graph Neural Networks with Global Attention

Parametric Contrastive Learning (ICCV2021)

Geometric Deep Learning for Flux

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

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

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

Disentagnled Graph Collaborative Filtering, SIGIR2020

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

[NeurIPS 2021] COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining

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

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)