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Graph neural networks A practical introduction to GNNs (2021) Spektral - Graph Neural Networks with Keras and Tensorflow 2. (Docs )A Comprehensive Survey on Graph Neural Networks (2019) Graph Neural Networks in TF2 Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels (2019) Strategies for Pre-training Graph Neural Networks Transformers are Graph Neural Networks (2020) (HN )Towards understanding glasses with graph neural networks (2020) How Powerful are Graph Neural Networks? Resources for learning Graph Neural Networks for beginners (2020) Graph-based Deep Learning Literature PyTorch Cluster - PyTorch Extension Library of Optimized Graph Cluster Algorithms.Graph Neural Network Model in TensorFlow Traffic prediction with advanced Graph Neural Networks (2020) (HN )Transformers Are Graph Neural Networks (2020) (HN )Must-read papers on graph neural networks Latest developments in Graph Neural Networks: A list of recent conference talks (2020) DGL-LifeSci - Python package for graph neural networks in chemistry and biology.Introduction to Graph Neural Networks (2020) PyDGN - Python library for Deep Graph Networks.A gentle introduction to deep learning for graphs (2020) Graph Structure of Neural Networks - PyTorch implementation.GraphGym - Platform for designing and evaluating Graph Neural Networks.GraphRNN - Generating Realistic Graphs with Deep Auto-regressive Model.Position-aware Graph Neural Networks SEAL - Learning from Subgraphs, Embeddings, and Attributes for Link prediction Jraph - Lightweight library for working with graph neural networks in jax.Benchmarking Graph Neural Networks (2020) (Code )Pro-GNN - PyTorch implementation of "Graph Structure Learning for Robust Graph Neural Networks".Supervised Learning on Relational Databases with Graph Neural Networks Why Iām lukewarm on graph neural networks (2020) (HN )Simplicial Neural Networks - Generalization of graph neural networks to data that live on a class of topological spaces called [simplicial complexes].FLAG: Adversarial Data Augmentation for Graph Neural Networks Distilling Knowledge From Graph Convolutional Networks (2020) (Code )GN-Transformer AST - Code for "GN-Transformer: Fusing AST and Source Code information in Graph Networks" paper.Graph theory, graph convolutional networks, knowledge graphs (2021) (HN )Theoretical Foundations of Graph Neural Networks (2021) PyTorch GAT - PyTorch implementation of the original GAT paper.Graph Transformer Networks (2019) (Code )DropEdge: Towards Deep Graph Convolutional Networks on Node Classification DIG (Dive into Graphs) - Library for graph deep learning research.Understanding Graph Neural Networks from Graph Signal Denoising Perspectives (2020) (Code )Adaptive Filters and Aggregator Fusion for Efficient Graph Convolutions Graph Convolutional Networks in PyTorch Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges (2021) E(n) Equivariant Graph Neural Networks (2021) (Code )How Attentive are Graph Attention Networks? (2021) (Code )Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification (2021) (Code )Binary Graph Neural Networks (2021) (Code )Scaling Graph Neural Networks with Approximate PageRank (2020) (Code )CS224W: Machine Learning with Graphs (2021) Graph Attention Networks (GAT) annotated implementation Awesome Explainable Graph Reasoning - Collection of research papers and software related to explainability in graph machine learning.An Attempt at Demystifying Graph Deep Learning Graph Random Neural Network for Semi-Supervised Learning on Graphs (2020) (Code )CapsGNN: Capsule Graph Neural Networks in PyTorch A Gentle Introduction to Graph Neural Networks (2021) Understanding Convolutions on Graphs (2021) GraphNeuralNetworks.jl - Graph Neural Networks in Julia.MilaGraph - Research group focusing on graph representation learning and graph neural networks.Modeling Relational Data with Graph Convolutional Networks (2017) (Code )GNNLens2 - Visualization tool for Graph Neural Networks.Hierarchical Graph Representation Learning with Differentiable Pooling (2018) (Code )VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization (2021) Pitfalls of Graph Neural Network Evaluation (2019) (Code )Understanding Pooling in Graph Neural Networks (2021) (Code )Spectral Clustering with Graph Neural Networks for Graph Pooling (2020) (Code )Graph Robustness Benchmark (GRB) - Scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.TensorFlow GNN - Library to build Graph Neural Networks on the TensorFlow platform. (Article )Graph Neural Networks through the lens of Differential Geometry and Algebraic Topology (2021) (Tweet )DGN - Graph convolutional reinforcement learning, where the multi-agent environment is modeled as a graph, each agent is a node, and the encoding of local observation of agent is the feature of node.SE(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials (2021) (Tweet )On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features (2021) (Tweet )Graph Neural Networks as Neural Diffusion PDEs (2021) PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT Exact Combinatorial Optimization with Graph Convolutional Neural Networks (2021) (Code )A Recipe for Training Neural Networks (2019) GraphSAINT: Graph Sampling Based Inductive Learning Method (2020) (Code )Decoupling the Depth and Scope of Graph Neural Networks (2021) (Code )How to Scale Up GNNs with Mini-Batch Sampling (2021) Papers about explainability of GNNs GraphGallery - Gallery for benchmarking Graph Neural Networks (GNNs).From Canonical Correlation Analysis to Self-supervised Graph Neural Networks (2021) (Code )Expressive Power of Invariant and Equivariant Graph Neural Networks (2021) (Code )Simple implementation of Equivariant GNN in PyTorch GemNet: Universal Directional Graph Neural Networks for Molecules (2021) (Code )Graph4NLP - Easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing.GNNs Recipe - Recipe to study Graph Neural Networks (GNNs).GraphiT: Encoding Graph Structure in Transformers (2021) (Code )Graph Neural Networks with Learnable Structural and Positional Representations (2022) (Code )Deep Learning on Graphs Book Graph Neural Networks: Foundations, Frontiers, and Applications (2022) Representing Long-Range Context for Graph Neural Networks with Global Attention CW Networks - Message Passing Neural Networks for Simplicial and Cell Complexes.GMAN: A Graph Multi-Attention Network for Traffic Prediction Awesome Efficient Graph Neural Networks GraphSAGE - Inductive Representation Learning on Large Graphs. (PyTorch Code )Topological Graph Neural Networks (2022) Heterogeneous Graph Neural Network Graph Condensation for Graph Neural Networks (2022) (Code )Awesome Self Supervised GNN - Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).ptgnn - PyTorch Graph Neural Network Library.BrainGB - Unified, modular, scalable, and reproducible framework established for brain network analysis with GNNs. (Web )Equilibrium Aggregation (2022) Awesome resources on Graph Neural Networks Graph Neural Networks with convolutional ARMA filters (2021) (Code )Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (2021) (Code )Geometric and Physical Quantities Improve E(3) Equivariant Message Passing (2021) (Code )Graph Attention Networks (2018) (Code )Directed Acyclic Graph Neural Networks (2022) (Code )Expressive GNNs and How To Tame Them (2022) (Tweet )Automated Self-Supervised Learning for Graphs (2022) (Code )Graph Neural PDEs Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs (2022) (Review )Sampling for Heterogeneous GNNs TensorFlow implementations of Graph Neural Networks gtrick - Bag of Tricks for Graph Neural Networks.How Airbnb is using Graph Convolutional Networks in production (2022) Foundations of Graph Neural Networks online course Basics of Graph Neural Networks Local Augmentation for Graph Neural Networks (2021) (Code )Awesome Expressive GNN Pure Transformers are Powerful Graph Learners (2022) (Code )Transformers Generalize DeepSets and Can be Extended to Graphs and Hypergraphs (2021) (Code )Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs (2020) (Code )M3GNet - Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.