← Search

Federico Di Valerio

2 accepted papers

2026

CIP-Net: Continual Interpretable Prototype-based Network

AAAI 2026technical

Continual learning constrains models to learn new tasks over time without forgetting what they have already learned. A key challenge in this setting is catastrophic forgetting, where learning new information causes the model to lose its performance on previous tasks. Recently, explainable AI has bee

Cited by 0SourcePDFScholar
2026

PPI Candidate Ranking: Large-Scale Evaluation of a Domain Knowledge–Guided Pipeline

ICML 2026poster

Computational approaches have become central to Protein–Protein Interaction (PPI) research, complementing experimental techniques that remain costly and incomplete. While modern deep learning methods capture diverse biological signals and hold promise in expanding the known interactome, empirical va…

Cited by 0SourceScholar