A Graph Embedding Approach to User Behavior Anomaly Detection. - Alexander Modell; Jonathan Larson; Melissa Turcotte; Anna Bertiger (IEEE BigData, 2021)

Implications of sparsity and high triangle density for graph representation learning. - Hannah Sansford; Alexander Modell; Nick Whiteley; Patrick Rubin-Delanchy (AISTATS, 2023)

Hierarchical clustering with dot products recovers hidden tree structure. - Annie Gray; Alexander Modell; Patrick Rubin-Delanchy; Nick Whiteley (NeurIPS, 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, 2023)

Entrywise error bounds for low-rank approximations of kernel matrices. - Alexander Modell (NeurIPS, 2024)

The Origins of Representation Manifolds in Large Language Models. - Alexander Modell; Patrick Rubin-Delanchy; Nick Whiteley (CoRR, 2025)

Multiresolution Analysis and Statistical Thresholding on Dynamic Networks. - Raphaël Romero; Tijl De Bie; Nick Heard; Alexander Modell (CoRR, 2025)