activity
20222026
most citedModular multi-source prediction of drug side-effects with DruGNN

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Dissecting Agentic Forensics: The Role of Triage, Prompting, and Evidence Arbitration in Open-World Fake Image Detection

Xianlong Li, Pietro Bongini, Niccoló Pancino +3

Image forensics is increasingly an open-world problem: manipulations range from fully synthetic images to localized edits, splicing and swapping, while most forensic detectors rema…

stat.ML2026

The Role of Input Dimensionality in the Emergence and Targeted Control of Adversarial Examples

Nasrin Malekzadeh Goradel, Niccolo Pancino, Yaser Gholizade Atani +3

Several theoretical works have tried to explain the adversarial vulnerability of deep neural networks through properties of high-dimensional geometry. However, the assumptions unde…

cs.LG2024

JMA: a General Algorithm to Craft Nearly Optimal Targeted Adversarial Example

Benedetta Tondi, Wei Guo, Niccolò Pancino +1

Most of the approaches proposed so far to craft targeted adversarial examples against Deep Learning classifiers are highly suboptimal and typically rely on increasing the likelihoo…

stat.ML2022★ 1 cited

A Deep Learning Approach to the Prediction of Drug Side-Effects on Molecular Graphs

Pietro Bongini, Elisa Messori, Niccolò Pancino +1

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. Automatic predictor…

q-bio.QM2022★ 1 cited

Modular multi-source prediction of drug side-effects with DruGNN

Pietro Bongini, Franco Scarselli, Monica Bianchini +3

Drug Side-Effects (DSEs) have a high impact on public health, care system costs, and drug discovery processes. Predicting the probability of side-effects, before their occurrence,…