
Learning to Learn Graph Topologies
Learning a graph topology to reveal the underlying relationship between ...
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Beltrami Flow and Neural Diffusion on Graphs
We propose a novel class of graph neural networks based on the discretis...
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Local2Global: Scaling global representation learning on graphs via local training
We propose a decentralised "local2global" approach to graph representati...
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Interpretable Stability Bounds for Spectral Graph Filters
Graphstructured data arise in a variety of realworld context ranging f...
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On the Stability of Graph Convolutional Neural Networks under Edge Rewiring
Graph neural networks are experiencing a surge of popularity within the ...
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Kernelbased Graph Learning from Smooth Signals: A Functional Viewpoint
The problem of graph learning concerns the construction of an explicit t...
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Graph signal processing for machine learning: A review and new perspectives
The effective representation, processing, analysis, and visualization of...
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Neural Architecture Search using Bayesian Optimisation with WeisfeilerLehman Kernel
Bayesian optimisation (BO) has been widely used for hyperparameter optim...
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Gaussian Processes on Graphs via Spectral Kernel Learning
We propose a graph spectrumbased Gaussian process for prediction of sig...
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A Maximum Entropy approach to Massive Graph Spectra
Graph spectral techniques for measuring graph similarity, or for learnin...
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Laplacianregularized graph bandits: Algorithms and theoretical analysis
We study contextual multiarmed bandit problems in the case of multiple ...
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Error Analysis on Graph Laplacian Regularized Estimator
We provide a theoretical analysis of the representation learning problem...
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Learning Quadratic Games on Networks
Individuals, or organizations, cooperate with or compete against one ano...
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Data for Refugees: The D4R Challenge on Mobility of Syrian Refugees in Turkey
The Data for Refugees (D4R) Challenge is a nonprofit challenge initiate...
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Learning Graphs from Data: A Signal Representation Perspective
The construction of a meaningful graph topology plays a crucial role in ...
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Entropic Spectral Learning in Large Scale Networks
We present a novel algorithm for learning the spectral density of large ...
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Learning heat diffusion graphs
Effective information analysis generally boils down to properly identify...
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Multimodal image retrieval with random walk on multilayer graphs
The analysis of large collections of image data is still a challenging p...
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Learning Laplacian Matrix in Smooth Graph Signal Representations
The construction of a meaningful graph plays a crucial role in the succe...
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Multiscale Event Detection in Social Media
Event detection has been one of the most important research topics in so...
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Clustering on MultiLayer Graphs via Subspace Analysis on Grassmann Manifolds
Relationships between entities in datasets are often of multiple nature,...
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Clustering with MultiLayer Graphs: A Spectral Perspective
Observational data usually comes with a multimodal nature, which means t...
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Xiaowen Dong
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