GNNPapers
by thunlp
Must-read papers on graph neural networks (GNN)
AI summary
Graph paper collection
A curated collection of must-read papers on graph neural networks, providing a comprehensive overview of the field.
- stars
- 16.1K
- forks
- 3K
- watching
- 600
- awesome list
- 1
Similar projects
Found by comparing what the projects do, not just their names.
Graph network benchmarking suite
A collection of datasets and tools for evaluating graph neural networks
tensorflow/gnn1.4K
Graph Network Library
Builds Graph Neural Networks on the TensorFlow platform using heterogeneous graphs and various machine learning techniques.
Deep Learning Papers Roadmap
A comprehensive roadmap for learning deep learning by following key papers in the field
Graph Neural Network Optimizer
Analyzes and optimizes the performance of graph neural networks using gradient boosting and various aggregation models.
GNNs
An implementation of graph neural networks for solving combinatorial optimization problems
Graph network builder
Builds graph networks in TensorFlow using a library provided by DeepMind's AI research organization.
Graph learning framework
A software framework that integrates statistical relational learning and graph neural networks for semi-supervised object classification and unsupervised node representation learning.
Deep learning implementations
Implementations of various deep learning algorithms and techniques with accompanying documentation
GNN viewer
An interactive visualization tool for graph neural networks
Paper Notes
A collection of notes and summaries on various deep learning research papers, including their topics, techniques, and applications.
Graph neural network library
A Python library for building graph neural networks with Keras and TensorFlow 2.
Graph Neural Network Model
A PyTorch implementation of a graph neural network model that learns personalized node representations
Graph algorithm
An implementation of a deep learning algorithm for graph data
Graph Neural Network Toolkit
An open-source toolkit for training and applying heterogeneous graph neural networks using PyTorch and the Deep Graph Library.
Graph CNN
A deep learning framework implementation of higher-order graph convolutional architectures and their applications
Featured in 1 awesome list
Each link jumps to the spot where the list mentions GNNPapers.
