3 papers
cs.LG2026
Applications of temporal graph learning for predicting the dynamics of biological systems
Manuel Dileo, Andrea Sottoriva
Biological foundation models have shown strong performance in single-cell representation learning by applying transformer architectures directly to gene-expression matrices. Howeve…
cs.LG2023
DURENDAL: Graph deep learning framework for temporal heterogeneous networks
Manuel Dileo, Matteo Zignani, Sabrina Gaito
Temporal heterogeneous networks (THNs) are evolving networks that characterize many real-world applications such as citation and events networks, recommender systems, and knowledge…
cs.LG2023
Temporal Smoothness Regularisers for Neural Link Predictors
Manuel Dileo, Pasquale Minervini, Matteo Zignani +1
Most algorithms for representation learning and link prediction on relational data are designed for static data. However, the data to which they are applied typically evolves over…