Imagenet classification with deep convolutional neural networks, NIPS, 2012. ,
Speech recognition with deep recurrent neural networks, 2013 IEEE international conference on acoustics, speech and signal processing, pp.6645-6649, 2013. ,
The graph neural network model, IEEE Transactions on Neural Networks, vol.20, issue.1, pp.61-80, 2009. ,
Neural message passing from quantum chemistry, Proceedings of the International Conference on Machine Learning, 2017. ,
Geometric deep learning: Going beyond euclidean data, IEEE Signal Processing Magazine, vol.34, issue.4, pp.18-42, 2017. ,
, A comprehensive survey on graph neural networks, 2019.
, Spectral networks and locally connected networks on graphs, 2013.
Convolutional neural networks on graphs with fast localized spectral filtering, Advances in Neural Information Processing Systems, pp.3844-3852, 2016. ,
Cayleynets: Graph convolutional neural networks with complex rational spectral filters, IEEE Transactions on Signal Processing, vol.67, issue.1, pp.97-109, 2019. ,
Semi-supervised classification with graph convolutional networks, International Conference on Learning Representations (ICLR, 2017. ,
Graph attention networks, International Conference on Learning Representations (ICLR), 2018. ,
Revisiting semisupervised learning with graph embeddings, Proceedings of the 33rd International Conference on International Conference on Machine Learning, ICML'16, 2016. ,
, A comprehensive survey on graph neural networks, 2019.
, Spectral graph theory, 1997.
The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains, IEEE signal processing magazine, vol.30, issue.3, pp.83-98, 2013. ,
Deep convolutional networks on graph-structured data, 2015. ,
Molecular graph convolutions: moving beyond fingerprints, Journal of computer-aided molecular design, vol.30, issue.8, pp.595-608, 2016. ,
Convolutional networks on graphs for learning molecular fingerprints, Advances in Neural Information Processing Systems, pp.2224-2232, 2015. ,
Learning convolutional neural networks for graphs, Proceedings of the International Conference on Machine Learning, pp.2014-2023, 2016. ,
A generalization of convolutional neuralnetworks to graph-structured data, 2017. ,
Diffusion-convolutional neural networks, Advances in Neural Information Processing Systems, pp.1993-2001, 2016. ,
Inductive representation learning on large graphs, Advances in Neural Information Processing Systems, pp.1024-1034, 2017. ,
Geometric deep learning on graphs and manifolds using mixture model cnns, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.5115-5124, 2017. ,
Splinecnn: Fast geometric deep learning with continuous b-spline kernels, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.869-877, 2018. ,
Empirical evaluation of rectified activations in convolutional network, 2015. ,
Dual-primal graph convolutional networks, 2018. ,
Wavelets on graphs via spectral graph theory, Applied and Computational Harmonic Analysis, vol.30, issue.2, pp.129-150, 2011. ,
URL : https://hal.archives-ouvertes.fr/inria-00541855
An end-to-end deep learning architecture for graph classification, Thirty-Second AAAI Conference on Artificial Intelligence, 2018. ,
Mixhop: Higher-order graph convolution architectures via sparsified neighborhood mixing, International Conference on Machine Learning (ICML), 2019. ,
Xception: Deep learning with depthwise separable convolutions, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.1251-1258, 2017. ,
, 2018 IEEE Conference on Computer Vision and Pattern Recognition, pp.4510-4520, 2018.
On the transferability of spectral graph filters, 2019. ,
Spectral multigraph networks for discovering and fusing relationships in molecules, 2018. ,
Predicting multicellular function through multi-layer tissue networks, Bioinformatics, vol.33, issue.14, pp.190-198, 2017. ,
Benchmark data sets for graph kernels, 2016. ,
Hierarchical graph representation learning with differentiable pooling, Advances in Neural Information Processing Systems, pp.4800-4810, 2018. ,
Towards sparse hierarchical graph classifiers, 2018. ,
Dissecting graph neural networks on graph classification, CoRR, 2019. ,
How powerful are graph neural networks?, in International Conference on Learning Representations, 2019. ,
Gaan: Gated attention networks for learning on large and spatiotemporal graphs, Conference on Uncertainty in Artificial Intelligence, UAI, 2018. ,