ON GRAPH CONVOLUTION FOR GRAPH CNNS
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Soummya Kar | José M. F. Moura | Jian Du | John Shi | S. Kar | Jian Du | John Shi
[1] Ruslan Salakhutdinov,et al. Revisiting Semi-Supervised Learning with Graph Embeddings , 2016, ICML.
[2] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[3] José M. F. Moura,et al. Discrete Signal Processing on Graphs: Frequency Analysis , 2013, IEEE Transactions on Signal Processing.
[4] José M. F. Moura,et al. Big Data Analysis with Signal Processing on Graphs: Representation and processing of massive data sets with irregular structure , 2014, IEEE Signal Processing Magazine.
[5] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[6] José M. F. Moura,et al. Discrete Signal Processing on Graphs , 2012, IEEE Transactions on Signal Processing.
[7] Joan Bruna,et al. Spectral Networks and Locally Connected Networks on Graphs , 2013, ICLR.
[8] Xavier Bresson,et al. Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering , 2016, NIPS.
[9] José M. F. Moura,et al. Graph Equivalence Classes for Spectral Projector-Based Graph Fourier Transforms , 2017, ArXiv.
[10] Jonathan Masci,et al. Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[11] Pascal Frossard,et al. The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains , 2012, IEEE Signal Processing Magazine.
[12] Soummya Kar,et al. Topology adaptive graph convolutional networks , 2017, ArXiv.
[13] Soummya Kar,et al. Convergence Analysis of Distributed Inference with Vector-Valued Gaussian Belief Propagation , 2016, J. Mach. Learn. Res..