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Graph similarity learning for change-point detection in dynamic networks


Mar 29, 2022
Deborah Sulem, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong

* 33 pages, 21 figures, 5 tables 

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Local2Global: A distributed approach for scaling representation learning on graphs


Jan 12, 2022
Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu

* 25 pages, 6 figures. arXiv admin note: substantial text overlap with arXiv:2107.12224 

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On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features


Dec 03, 2021
Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael Bronstein


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Understanding over-squashing and bottlenecks on graphs via curvature


Nov 29, 2021
Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein


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Adversarial Attacks on Graph Classification via Bayesian Optimisation


Nov 04, 2021
Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong

* NeurIPS 2021. 11 pages, 8 figures, 2 tables (24 pages, 17 figures, 8 tables including references and appendices) 

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Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets


Oct 25, 2021
Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong


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Learning to Learn Graph Topologies


Oct 19, 2021
Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen

* Accepted at NeurIPS 2021 

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Beltrami Flow and Neural Diffusion on Graphs


Oct 18, 2021
Benjamin Paul Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M Bronstein

* 21 pages, 5 figures. Proceedings of the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021 

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Local2Global: Scaling global representation learning on graphs via local training


Jul 26, 2021
Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu

* 5 pages, 1 figure, to appear at DLG-KDD '21 

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Interpretable Stability Bounds for Spectral Graph Filters


Feb 18, 2021
Henry Kenlay, Dorina Thanou, Xiaowen Dong


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On the Stability of Graph Convolutional Neural Networks under Edge Rewiring


Oct 26, 2020
Henry Kenlay, Dorina Thanou, Xiaowen Dong


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Kernel-based Graph Learning from Smooth Signals: A Functional Viewpoint


Aug 23, 2020
Xingyue Pu, Siu Lun Chau, Xiaowen Dong, Dino Sejdinovic

* 13 pages, with extra 3-page appendices 

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Graph signal processing for machine learning: A review and new perspectives


Jul 31, 2020
Xiaowen Dong, Dorina Thanou, Laura Toni, Michael Bronstein, Pascal Frossard


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Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel


Jun 13, 2020
Binxin Ru, Xingchen Wan, Xiaowen Dong, Michael Osborne

* 8 pages, 4 figures (21 pages, 13 figures including references and appendices) 

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Gaussian Processes on Graphs via Spectral Kernel Learning


Jun 12, 2020
Yin-Cong Zhi, Yin Cheng Ng, Xiaowen Dong

* 13 pages, 5 Figures 

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A Maximum Entropy approach to Massive Graph Spectra


Dec 19, 2019
Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael Osborne, Stephen Roberts

* 12 pages. 9 Figures 

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Laplacian-regularized graph bandits: Algorithms and theoretical analysis


Jul 12, 2019
Kaige Yang, Xiaowen Dong, Laura Toni


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Error Analysis on Graph Laplacian Regularized Estimator


Feb 11, 2019
Kaige Yang, Xiaowen Dong, Laura Toni


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Learning Quadratic Games on Networks


Nov 21, 2018
Yan Leng, Xiaowen Dong, Alex Pentland


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Learning Graphs from Data: A Signal Representation Perspective


Jun 03, 2018
Xiaowen Dong, Dorina Thanou, Michael Rabbat, Pascal Frossard


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Entropic Spectral Learning in Large Scale Networks


Apr 18, 2018
Diego Granziol, Binxin Ru, Stefan Zohren, Xiaowen Dong, Michael Osborne, Stephen Roberts

* 11 pages, 8 figures 

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Learning heat diffusion graphs


Nov 04, 2016
Dorina Thanou, Xiaowen Dong, Daniel Kressner, Pascal Frossard


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Multi-modal image retrieval with random walk on multi-layer graphs


Jul 12, 2016
Renata Khasanova, Xiaowen Dong, Pascal Frossard


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Learning Laplacian Matrix in Smooth Graph Signal Representations


Feb 19, 2016
Xiaowen Dong, Dorina Thanou, Pascal Frossard, Pierre Vandergheynst


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Multiscale Event Detection in Social Media


Feb 06, 2015
Xiaowen Dong, Dimitrios Mavroeidis, Francesco Calabrese, Pascal Frossard

* Data Mining and Knowledge Discovery, vol. 29, no. 5, pp. 1374-1405, September 2015 

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Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds


Mar 09, 2013
Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov

* IEEE Transactions on Signal Processing, vol. 62, no. 4, pp. 905-918, February 2014 

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Clustering with Multi-Layer Graphs: A Spectral Perspective


Jun 11, 2011
Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov

* IEEE Transactions on Signal Processing, vol. 60, no. 11, pp. 5820-5831, November 2012 

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