28 citations · 49 across the 17 of their papers we have counts for
4 papers · 1 filter
ASIF: Coupled Data Turns Unimodal Models to Multimodal Without Training
Antonio Norelli, Marco Fumero, Valentino Maiorca +3
CLIP proved that aligning visual and language spaces is key to solving many vision tasks without explicit training, but required to train image and text encoders from scratch on a…
Sparse Vicious Attacks on Graph Neural Networks
Giovanni Trappolini, Valentino Maiorca, Silvio Severino +3
Graph Neural Networks (GNNs) have proven to be successful in several predictive modeling tasks for graph-structured data. Amongst those tasks, link prediction is one of the fundame…
Relative representations enable zero-shot latent space communication
Luca Moschella, Valentino Maiorca, Marco Fumero +3
Neural networks embed the geometric structure of a data manifold lying in a high-dimensional space into latent representations. Ideally, the distribution of the data points in the…
Metric Based Few-Shot Graph Classification
Donato Crisostomi, Simone Antonelli, Valentino Maiorca +3
Many modern deep-learning techniques do not work without enormous datasets. At the same time, several fields demand methods working in scarcity of data. This problem is even more c…