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Andreas Loukas

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Andreas Loukas

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Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions

SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators

Partition and Code: learning how to compress graphs

Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs

Dynamic Balanced Graph Partitioning

Graph Coarsening with Preserved Spectral Properties

On the Relationship between Self-Attention and Convolutional Layers

What graph neural networks cannot learn: depth vs width

How hard is to distinguish graphs with graph neural networks?

Stationary time-vertex signal processing