2 citations · 4 across the 3 of their papers we have counts for
3 papers
Pointspectrum: Equivariance Meets Laplacian Filtering for Graph Representation Learning
Marinos Poiitis, Pavlos Sermpezis, Athena Vakali
Graph Representation Learning (GRL) has become essential for modern graph data mining and learning tasks. GRL aims to capture the graph's structural information and exploit it in c…
What training reveals about neural network complexity
Andreas Loukas, Marinos Poiitis, Stefanie Jegelka
This work explores the Benevolent Training Hypothesis (BTH) which argues that the complexity of the function a deep neural network (NN) is learning can be deduced by its training d…
On the Aggression Diffusion Modeling and Minimization in Online Social Networks
Marinos Poiitis, Athena Vakali, Nicolas Kourtellis
Aggression in online social networks has been studied mostly from the perspective of machine learning which detects such behavior in a static context. However, the way aggression d…