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Visual Question Answering for Cultural Heritage
This will turn the classic audio guide into a smart personal instructor with which the visitor can interact by asking for explanations focused on specific interests.
Molecular graph generation with Graph Neural Networks
The use of graph neural networks maximizes the information in input at each generative step, which consists of the subgraph produced during the previous steps.
Modular multi-source prediction of drug side-effects with DruGNN
Drug Side-Effects (DSEs) have a high impact on public health, care system costs, and drug discovery processes.
Is GPT-3 all you need for Visual Question Answering in Cultural Heritage?
The use of Deep Learning and Computer Vision in the Cultural Heritage domain is becoming highly relevant in the last few years with lots of applications about audio smart guides, interactive museums and augmented reality.
A Deep Learning Approach to the Prediction of Drug Side-Effects on Molecular Graphs
Predicting drug side-effects before they occur is a key task in keeping the number of drug-related hospitalizations low and to improve drug discovery processes.
