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20172025
most citedImproving Graph Neural Network Expressivity via Subgraph Isomorphism Counting

297 citations · 434 across the 14 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

cs.CV2020

3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties

Soha Sadat Mahdi, Nele Nauwelaers, Philip Joris +8

Face recognition is a widely accepted biometric verification tool, as the face contains a lot of information about the identity of a person. In this study, a 2-step neural-based pi…

cs.CV2020

Learning to Generate Customized Dynamic 3D Facial Expressions

Rolandos Alexandros Potamias, Jiali Zheng, Stylianos Ploumpis +3

Recent advances in deep learning have significantly pushed the state-of-the-art in photorealistic video animation given a single image. In this paper, we extrapolate those advances…

cs.LG2020★ 81 cited

Deep Polynomial Neural Networks

Grigorios Chrysos, Stylianos Moschoglou, Giorgos Bouritsas +3

Deep Convolutional Neural Networks (DCNNs) are currently the method of choice both for generative, as well as for discriminative learning in computer vision and machine learning. T…

cs.LG2020★ 297 cited

Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting

Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou +1

While Graph Neural Networks (GNNs) have achieved remarkable results in a variety of applications, recent studies exposed important shortcomings in their ability to capture the stru…

cs.LG2020

nets: Deep Polynomial Neural Networks

Grigorios G. Chrysos, Stylianos Moschoglou, Giorgos Bouritsas +3

Deep Convolutional Neural Networks (DCNNs) is currently the method of choice both for generative, as well as for discriminative learning in computer vision and machine learning. Th…