- Geometric deep learning: going beyond Euclidean data (IEEE Signal Processing Magazine 2017)
- Graph Neural Networks: A Review of Methods and Applications (2019)
- A Comprehensive Survey on Graph Neural Networks (2019)
- The graph neural network model (2009)
- Spectral Networks and Locally Connected Networks on Graphs (ICLR 2014)
- Deep Convolutional Networks on Graph-Structured Data (arXiv 2015)
- Diffusion-Convolutional Neural Networks (2015)
- Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering (NIPS 2016)
- Semi-Supervised Classification with Graph Convolutional Networks (ICLR 2017)
- Convolutional Networks on Graphs for Learning Molecular Fingerprints (NIPS 2015)
- Geodesic Convolutional Neural Networks on Riemannian Manifolds (3dRR 2015)
- Learning shape correspondence with anisotropic convolutional neural networks (NIPS 2016)
- Discriminative embeddings of latent variable models for structured data (ICML 2016)
- SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels (CVPR 2018)
- Neural Message Passing for Quantum Chemistry (ICML 2017)
- Graph Attention Networks (ICLR 2018)
- Weisfeiler and Lemon Go Neural: Higher-order Graph Neural Networks (AAAI 2019)
- How Powerful are Graph Neural Networks? (ICLR 2019)
- Graph Neural Networks with Convolutional ARMA Filters (CoRR 2019)
- Simplifying Graph Convolutional Networks (CoRR 2019)
- Combining Neural Networks with Personalized PageRank for Classification on Graphs (ICLR 2019)
- Attention-based Graph Neural Networks for Semi-Supervised Learning (CoRR 2017)
- Modeling Relational Data with Graph Convolutional Networks (ESWC 2018)
- Dynamic Graph CNN for Learning on Point Clouds (CoRR 2018)
- PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation (CVPR 2017)
- PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space (NIPS 2017)
- PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
- Geometric Deep Learning on Graphs and Manifolds using Mixture Model CNNs (CVPR 2017)
- SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation (CVPR 2017)
- Relational Inductive Biases, Deep Learning, and Graph Networks (CoRR 2018)
- Gated Graph Sequence Neural Networks (ICLR 2016)
- Order Matters: Sequence to Sequence for Sets (ICLR 2016)
- Structured Sequence Modeling with Graph Convolutional Recurrent Networks (2015)
- Deep Learning on Lie Groups for Skeleton-based Action Recognition (CVPR 2017)
- Geometric matrix completion with recurrent multi-graph neural networks (NIPS 2017)
- Deep Functional Maps: Structured Prediction for Dense Shape Correspondence (2017)
- CayleyNets: Graph convolutional neural networks with complex rational spectral filters (2017)
- Deriving Neural Architectures from Sequence and Graph Kernels (ICML 2017)
- SchNet: A continuous-filter convolutional neural network for modeling quantum interactions (NIPS 2017)
- Convolutional Neural Networks on Surfaces via Seamless Toric Covers (2017)
- Weighted Graph Cuts without Eigenvectors: A Multilevel Approach (PAMI 2007)
- An End-to-End Deep Learning Architecture for Graph Classification (AAAI 2018)
- Hierarchical Graph Representation Learning with Differentiable Pooling (NeurIPS 2018)
- Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs (CVPR 2017)
- Towards Sparse Hierarchical Graph Classifiers (NeurIPS-W 2018)
- Deep Graph Infomax (ICLR 2019)
- Graph U-Net (ICLR 2019 Submission)
- Inductive Representation Learning on Large Graphs (NIPS 2017)
- Learning Convolutional Neural Networks for Graphs (ICML 2016)
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