201 Open source projects that are alternatives of or similar to SelfGNN

ProteinGCN: Protein model quality assessment using Graph Convolutional Networks

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

Implementation of the WSDM 2021 paper "Node Similarity Preserving 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.

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

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

A distributed graph deep learning framework.

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

StellarGraph - Machine Learning on Graphs

A collection of important graph embedding, classification and representation learning papers with implementations.

Code and resources on scalable and efficient Graph Neural Networks

Summary of open source code for deep learning models in the field of traffic prediction

Graph Neural Network Library for PyTorch

Awesome Graph Self-Supervised Learning

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

A reading list for deep graph learning acceleration.

A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!

Representation Learning on Graphs with Jumping Knowledge Networks

links to conference publications in graph-based deep learning

Tutorials for Machine Learning on Graphs

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

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

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).

Code for Graph Convolutional Matrix Factorization for Bipartite Edge Prediction

Demo of RouteNet in ACM SIGCOMM'19

Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation, AAAI 2020

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

The implement of GNN based on Pytorch

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

This is an official implementation for "SimMIM: A Simple Framework for Masked Image Modeling".

GraphNVP: An Invertible Flow Model for Generating Molecular Graphs

Tensorflow Implementation of the paper "Topology Adaptive Graph Convolutional Networks" (Du et al., 2017)

[CVPR 2020] Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation (PyTorch)

[CVPR 2020] L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks

[ICRA 2020] Train generalizable policies for kit assembly with self-supervised dense correspondence learning.

A graph-based deep learning framework for life science

ACL 2018: Dating Documents using Graph Convolution Networks

Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

official implemntation for "Contrastive Learning with Stronger Augmentations"

📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).

PyTorch implementation of our paper "Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing" (NAACL19)

Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach, AAAI2020

Code for the BMVC paper (http://bmvc2018.org/contents/papers/1003.pdf)

TypeDB-ML is the Machine Learning integrations library for TypeDB

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

Neural Relation Understanding: neural cardinality estimators for tabular data

Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.

The official code and datasets for "Zero-Shot Multi-View Indoor Localization via Graph Location Networks" (ACMMM 2020)

⚡ Using deep learning (MLP, CNN, Graph CNN) to classify text in TensorFlow.

A list of data mining and machine learning papers that I implemented in 2019.

Official repository for the paper "Learning Local Neighboring Structure for Robust 3D Shape Representation"

This project is a collection of recent research in areas such as new infrastructure and urban computing, including white papers, academic papers, AI lab and dataset etc.

Visualization tool for Graph Neural Networks

Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks

Chainer implementation of 'Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering' (https://arxiv.org/abs/1606.09375)

A tutorial & minimal example (8min on CPU) for Graph Convolutional Networks for Text Classification. AAAI 2019

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)

PyTorch Implementation of GraphTSNE, ICLR’19

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