3 papers
stat.ME2026
Statistical hypothesis testing for differences between layers in dynamic multiplex networks
Maximilian Baum, Francesco Sanna Passino, Axel Gandy
With the emergence of dynamic multiplex networks, corresponding to graphs where multiple types of edges evolve over time, a key inferential task is to determine whether the layers…
stat.ME2026
Doubly unfolded adjacency spectral embedding of dynamic multiplex graphs
Maximilian Baum, Francesco Sanna Passino, Axel Gandy
Many real-world networks evolve dynamically over time and present different types of connections between nodes, often called layers. In this work, we propose a latent position mode…
stat.ME2026
Recovering manifold structure in LLM responses through a joint Euclidean mirror
Maximilian Baum, Aranyak Acharyya, Tianyi Chen +5
Understanding the behavior of black-box large language models and determining effective means of comparing their performance is a key task in modern machine learning. We consider h…