most citedPredicting Tweet Engagement with Graph Neural Networks

14 citations · 23 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SI2023★ 14 cited

Predicting Tweet Engagement with Graph Neural Networks

Marco Arazzi, Marco Cotogni, Antonino Nocera +1

Social Networks represent one of the most important online sources to share content across a world-scale audience. In this context, predicting whether a post will have any impact i…

cs.CV2022★ 1 cited

Exemplar-free Continual Learning of Vision Transformers via Gated Class-Attention and Cascaded Feature Drift Compensation

Marco Cotogni, Fei Yang, Claudio Cusano +2

We propose a new method for exemplar-free class incremental training of ViTs. The main challenge of exemplar-free continual learning is maintaining plasticity of the learner withou…

cs.CV2022★ 1 cited

Explaining Image Enhancement Black-Box Methods through a Path Planning Based Algorithm

Marco Cotogni, Claudio Cusano

Nowadays, image-to-image translation methods, are the state of the art for the enhancement of natural images. Even if they usually show high performance in terms of accuracy, they…

cs.CV2022★ 6 cited

Offset equivariant networks and their applications

Marco Cotogni, Claudio Cusano

In this paper we present a framework for the design and implementation of offset equivariant networks, that is, neural networks that preserve in their output uniform increments in…

cs.CV2022★ 1 cited

TreEnhance: A Tree Search Method For Low-Light Image Enhancement

Marco Cotogni, Claudio Cusano

In this paper we present TreEnhance, an automatic method for low-light image enhancement capable of improving the quality of digital images. The method combines tree search theory,…