This part refers to [awesome-auto-graph-learning] and adds some new works.
Source: PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm
- PaSca a Graph Neural Architecture Search System under the Scalable Paradigm [WWW 2022] [paper] [code]
- Designing the Topology of Graph Neural Networks A Novel Feature Fusion Perspective [WWW 2022] [paper]
- AutoHEnsGNN Winning Solution to AutoGraph Challenge for KDD Cup 2020 [ICDE 2022] [paper] [code]
- Auto-GNAS: A Parallel Graph Neural Architecture Search Framework [TPDS 2022] [paper] [code]
- Profiling the Design Space for Graph Neural Networks based Collaborative Filtering [WSDM 2022] [paper] [code]
- Graph Differentiable Architecture Search with Structure Learning [NeurIPS 2021] [paper] [code]
- AutoGEL: An Automated Graph Neural Network with Explicit Link Information [NeurIPS 2021] [paper] [code]
- Heterogeneous Graph Neural Architecture Search [ICDM 2021] [paper]
- Automated Graph Representation Learning for Node Classification [IJCNN 2021] [paper]
- ALGNN Auto-Designed Lightweight Graph Neural Network [PRICAI 2021] [paper]
- Pooling Architecture Search for Graph Classification [CIKM 2021] [paper] [code]
- DiffMG Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks [KDD 2021] [paper] [code]
- Learn Layer-wise Connections in Graph Neural Networks [KDD 2021 DLG Workshop] [paper]
- AutoAttend Automated Attention Representation Search [ICML 2021] [paper] [code]
- GraphPAS Parallel Architecture Search for Graph Neural Networks [SIGIR 2021] [paper]
- Rethinking Graph Neural Network Search from Message-passing [CVPR 2021] [paper] [code]
- Fitness Landscape Analysis of Graph Neural Network Architecture Search Spaces [GECCO 2021] [paper] [code]
- Learned low precision graph neural networks [EuroSys 2021 EuroMLSys workshop] [paper]
- Autostg: Neural architecture search for predictions of spatio-temporal graphs [WWW 2021] [paper] [code]
- Search to aggregate neighborhood for graph neural network [ICDE 2021] [paper] [code]
- One-shot graph neural architecture search with dynamic search space [AAAI 2021] [paper]
- Search For Deep Graph Neural Networks [Arxiv 2021] [paper]
- G-CoS GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency [ICCAD 2021] [paper]
- Edge-featured Graph Neural Architecture Search [Arxiv 2021] [paper]
- FL-AGCNS: Federated Learning Framework for Automatic Graph Convolutional Network Search [Arxiv 2021] [paper] [code]
- Graph Neural Architecture Search [IJCAI 2020] [paper] [code]
- Design space for graph neural networks [NeurIPS 2020] [paper] [code]
- Autograph: Automated graph neural network [ICONIP 2020] [paper]
- Graph neural network architecture search for molecular property prediction [BigData 2020] [paper] [code]
- Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network [CIKM 2020] [paper] [code]
- Simplifying architecture search for graph neural network [CIKM 2020 CSSA workshop] [paper] [code]
- Neural architecture search in graph neural networks [BRACIS 2020] [paper] [code]
- SGAS: Sequential Greedy Architecture Search [CVPR 2020] [paper] [code]
- Learning graph convolutional network for skeleton-based human action recognition by neural searching [AAAI 2020] [paper] [code]
- Efficient graph neural architecture search [OpenReview 2020] [paper]
- Evolutionary architecture search for graph neural networks [Arxiv 2020] [paper] [code]
- Probabilistic dual network architecture search on graphs [Arxiv 2020] [paper]
- Auto-GNN: Neural Architecture Search of Graph Neural Networks [Arxiv 2019] [paper]
Source: AutoNE: Hyperparameter optimization for massive network embedding
- Explainable Automated Graph Representation Learning with Hyperparameter Importance [ICML 2021] [paper]
- Automated Graph Learning via Population Based Self-Tuning GCN [SIGIR 2021] [paper]
- Automatic Graph Learning with Evolutionary Algorithms: An Experimental Study [PRICAI 2021] [paper]
- Which Hyperparameters to Optimise? An Investigation of Evolutionary Hyperparameter Optimisation in Graph Neural Network For Molecular Property Prediction [GECCO 2021] [paper]
- ASFGNN Automated separated-federated graph neural network [P2PNA 2021] [paper]
- A novel genetic algorithm with hierarchical evaluation strategy for hyperparameter optimisation of graph neural networks [Arxiv 2021] [paper]
- Jitune: Just-in-time hyperparameter tuning for network embedding algorithms [Arxiv 2021] [paper]
- Autonomous graph mining algorithm search with best speed/accuracy trade-off [ICDM 2020] [paper] [code]
- Automated Machine Learning on Graphs: A Survey [IJCAI 2021] [paper]
- Graph Neural Networks: AutoML [Springer 2022][paper]