1. Muhammet Balcilar Guillaume Renton Pierre Héroux Benoit Gaüzère Sébastien Adam and Paul Honeine. 2021. Analyzing the expressive power of graph neural networks in a spectral perspective. In ICLR. Muhammet Balcilar Guillaume Renton Pierre Héroux Benoit Gaüzère Sébastien Adam and Paul Honeine. 2021. Analyzing the expressive power of graph neural networks in a spectral perspective. In ICLR.
2. Filippo Maria Bianchi Daniele Grattarola and Cesare Alippi. 2020. Spectral clustering with graph neural networks for graph pooling. In ICML. Filippo Maria Bianchi Daniele Grattarola and Cesare Alippi. 2020. Spectral clustering with graph neural networks for graph pooling. In ICML.
3. Deyu Bo Xiao Wang Chuan Shi and Huawei Shen. 2021. Beyond Low-frequency Information in Graph Convolutional Networks. In AAAI. Deyu Bo Xiao Wang Chuan Shi and Huawei Shen. 2021. Beyond Low-frequency Information in Graph Convolutional Networks. In AAAI.
4. Aleksandar Bojchevski and Stephan Günnemann. 2018. Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking. In ICLR. Aleksandar Bojchevski and Stephan Günnemann. 2018. Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking. In ICLR.
5. Lei Chen Zhengdao Chen and Joan Bruna. 2021. On Graph Neural Networks versus Graph-Augmented MLPs. In ICLR. Lei Chen Zhengdao Chen and Joan Bruna. 2021. On Graph Neural Networks versus Graph-Augmented MLPs. In ICLR.