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Awesome-Auto-GNNs

Contents

This part refers to [awesome-auto-graph-learning] and adds some new works.

Graph Neural Architecture Search


Source: PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm

2022

  1. PaSca a Graph Neural Architecture Search System under the Scalable Paradigm [WWW 2022] [paper] [code]
  2. Designing the Topology of Graph Neural Networks A Novel Feature Fusion Perspective [WWW 2022] [paper]
  3. AutoHEnsGNN Winning Solution to AutoGraph Challenge for KDD Cup 2020 [ICDE 2022] [paper] [code]
  4. Auto-GNAS: A Parallel Graph Neural Architecture Search Framework [TPDS 2022] [paper] [code]
  5. Profiling the Design Space for Graph Neural Networks based Collaborative Filtering [WSDM 2022] [paper] [code]

2021

  1. Graph Differentiable Architecture Search with Structure Learning [NeurIPS 2021] [paper] [code]
  2. AutoGEL: An Automated Graph Neural Network with Explicit Link Information [NeurIPS 2021] [paper] [code]
  3. Heterogeneous Graph Neural Architecture Search [ICDM 2021] [paper]
  4. Automated Graph Representation Learning for Node Classification [IJCNN 2021] [paper]
  5. ALGNN Auto-Designed Lightweight Graph Neural Network [PRICAI 2021] [paper]
  6. Pooling Architecture Search for Graph Classification [CIKM 2021] [paper] [code]
  7. DiffMG Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks [KDD 2021] [paper] [code]
  8. Learn Layer-wise Connections in Graph Neural Networks [KDD 2021 DLG Workshop] [paper]
  9. AutoAttend Automated Attention Representation Search [ICML 2021] [paper] [code]
  10. GraphPAS Parallel Architecture Search for Graph Neural Networks [SIGIR 2021] [paper]
  11. Rethinking Graph Neural Network Search from Message-passing [CVPR 2021] [paper] [code]
  12. Fitness Landscape Analysis of Graph Neural Network Architecture Search Spaces [GECCO 2021] [paper] [code]
  13. Learned low precision graph neural networks [EuroSys 2021 EuroMLSys workshop] [paper]
  14. Autostg: Neural architecture search for predictions of spatio-temporal graphs [WWW 2021] [paper] [code]
  15. Search to aggregate neighborhood for graph neural network [ICDE 2021] [paper] [code]
  16. One-shot graph neural architecture search with dynamic search space [AAAI 2021] [paper]
  17. Search For Deep Graph Neural Networks [Arxiv 2021] [paper]
  18. G-CoS GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency [ICCAD 2021] [paper]
  19. Edge-featured Graph Neural Architecture Search [Arxiv 2021] [paper]
  20. FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search [Arxiv 2021] [paper] [code]

2020

  1. Graph Neural Architecture Search [IJCAI 2020] [paper] [code]
  2. Design space for graph neural networks [NeurIPS 2020] [paper] [code]
  3. Autograph: Automated graph neural network [ICONIP 2020] [paper]
  4. Graph neural network architecture search for molecular property prediction [BigData 2020] [paper] [code]
  5. Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network [CIKM 2020] [paper] [code]
  6. Simplifying architecture search for graph neural network [CIKM 2020 CSSA workshop] [paper] [code]
  7. Neural architecture search in graph neural networks [BRACIS 2020] [paper] [code]
  8. SGAS: Sequential Greedy Architecture Search [CVPR 2020] [paper] [code]
  9. Learning graph convolutional network for skeleton-based human action recognition by neural searching [AAAI 2020] [paper] [code]
  10. Efficient graph neural architecture search [OpenReview 2020] [paper]
  11. Evolutionary architecture search for graph neural networks [Arxiv 2020] [paper] [code]
  12. Probabilistic dual network architecture search on graphs [Arxiv 2020] [paper]

2019

  1. Auto-GNN: Neural Architecture Search of Graph Neural Networks [Arxiv 2019] [paper]

Graph Hyper-Parameter Optimization


Source: AutoNE: Hyperparameter optimization for massive network embedding

2021

  1. Explainable Automated Graph Representation Learning with Hyperparameter Importance [ICML 2021] [paper]
  2. Automated Graph Learning via Population Based Self-Tuning GCN [SIGIR 2021] [paper]
  3. Automatic Graph Learning with Evolutionary Algorithms: An Experimental Study [PRICAI 2021] [paper]
  4. Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction [GECCO 2021] [paper]
  5. ASFGNN Automated separated-federated graph neural network [P2PNA 2021] [paper]
  6. A novel genetic algorithm with hierarchical evaluation strategy for hyperparameter optimisation of graph neural networks [Arxiv 2021] [paper]
  7. Jitune: Just-in-time hyperparameter tuning for network embedding algorithms [Arxiv 2021] [paper]

2020

  1. Autonomous graph mining algorithm search with best speed/accuracy trade-off [ICDM 2020] [paper] [code]

2019

  1. AutoNE: Hyperparameter optimization for massive network embedding [KDD 2019] [paper] [code]

Survey

  1. Automated Machine Learning on Graphs: A Survey [IJCAI 2021] [paper]
  2. Graph Neural Networks: AutoML [Springer 2022][paper]

Tool

  1. PaSca a Graph Neural Architecture Search System under the Scalable Paradigm [WWW 2022] [paper] [code][doc]

  2. AutoGL: A Library for Automated Graph Learning [ICLR 2021 GTRL workshop] [paper] [code] [homepage]