Emma Ceccherini — accepted AI-conference papers

2025

Unsupervised Attributed Dynamic Network Embedding with Stability Guarantees

Emma Ceccherini, Ian Gallagher, Andrew Jones, Daniel John Lawson

UAI 2025

Stability for dynamic network embeddings ensures that nodes behaving the same at different times receive the same embedding, allowing comparison of nodes in the network across time. We present attributed unfolded adjacency spectral embedding (AUASE), a stable unsupervised representation learning fra

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2023

Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks

Alexander Modell, Ian Gallagher, Emma Ceccherini, Nick Whiteley, Patrick Rubin-Delanchy

NeurIPS 2023poster

We present a new representation learning framework, Intensity Profile Projection, for continuous-time dynamic network data. Given triples $(i,j,t)$, each representing a time-stamped ($t$) interaction between two entities ($i,j$), our procedure returns a continuous-time trajectory for each node, repr…

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