Baum, M., Sanna Passino, F., and Gandy, A. (2024), Doubly unfolded adjacency spectral embedding of dynamic multiplex graphs (arXiv , code ),
Ghani, D., Heard, N. A., and Sanna Passino, F. (2024), Approximate learning of parsimonious Bayesian context trees (arXiv , code ),
Martin, B., Sanna Passino, F., Cucuringu, M., and Luati, A. (2024), NIRVAR: Network Informed Restricted Vector Autoregression (arXiv , code ).
Journal articles and conference proceedings
Acharyya, A., Sanna Passino, F., Trosset, M. W., and Priebe, C. E. (2026), Convergence guarantees for response prediction in latent structure network time series, IEEE Transactions on Network Science and Engineering 13, 878-888 (paper , arXiv , code ),
Corneck, J., Cohen, E. A. K., Martin, J., Patel, L., Shuler, K. W., and Sanna Passino, F. (2025), Simultaneous global and local clustering in multiplex networks with covariate information, Journal of Complex Networks, to appear (arXiv , code ),
Martin, B., Cucuringu, M., Luati, A., and Sanna Passino, F. (2025), Factor-Driven Network Informed Restricted Vector Autoregression, ICAIF ‘25: Proceedings of the 6th ACM International Conference on AI in Finance, 431-439 (paper , arXiv , code ),
Corneck, J., Cohen, E. A. K., Martin, J., and Sanna Passino, F. (2025), Online Bayesian changepoint detection for network Poisson processes with community structure, Statistics and Computing, 35(75) (paper , arXiv , code ),
Sanna Passino, F., Mantziou, A., Ghani, D., Thiede, P., Bevington, R., and Heard, N. A. (2025), Nested Dirichlet models for unsupervised attack pattern detection in honeypot data, Annals of Applied Statistics 19(1), 586-613 (paper , arXiv , code ),
Li, X. V., and Sanna Passino, F. (2024), FinDKG: Dynamic Knowledge Graphs with Large Language Models for Detecting Global Trends in Financial Markets, ICAIF ‘24: Proceedings of the 5th ACM International Conference on AI in Finance, 573-581 (paper , arXiv , code , webpage , model ),
September, M. A. K., Sanna Passino, F., Goldmann, L., and Hinel, A. (2024), Extended Deep Adaptive Input Normalization for Preprocessing Time Series Data for Neural Networks, Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), Vol. 238, 1891–1899 (paper , arXiv , code ),
Sanna Passino, F., Che, Y., and Cardoso Correia Perello, C. (2024), Graph-based mutually exciting point processes for modelling event times in docked bike-sharing systems, Stat 13(1), e660 (paper , arXiv , code ),
Sanna Passino, F. and Heard, N. A. (2023), Mutually exciting point process graphs for modelling dynamic networks, Journal of Computational and Graphical Statistics 32(1), 116-130 (paper , arXiv , code , video ),
Sanna Passino, F. and Heard, N. A. (2022), Latent structure blockmodels for Bayesian spectral graph clustering, Statistics and Computing 32(2) (paper , arXiv , code ),
Sanna Passino, F., Heard, N. A. and Rubin-Delanchy, P. (2022), Spectral clustering on spherical coordinates under the degree-corrected stochastic blockmodel, Technometrics 64(3), 346-357 (paper , arXiv , code ),
Sanna Passino, F., Turcotte, M. J. M. and Heard, N. A. (2022), Graph link prediction in computer networks using Poisson matrix factorisation, Annals of Applied Statistics 16(3), 1313-1332 (paper , arXiv ),
Sanna Passino, F., Bertiger, A. S., Neil, J. C. and Heard, N. A. (2021), Link prediction in dynamic networks using random dot product graphs, Data Mining and Knowledge Discovery 35(5), 2168-2199 (paper , arXiv ),
Sanna Passino, F., Maystre, L., Moor, D., Anderson, A. and Lalmas, M. (2021), Where To Next? A Dynamic Model of User Preferences, Proceedings of The Web Conference 2021 - TheWebConf21 (paper , paper , blog , video ),
Sanna Passino, F. and Heard, N. A. (2020), Bayesian estimation of the latent dimension and communities in stochastic blockmodels, Statistics and Computing 30(5), 1291-1307 (paper , arXiv , code ),
Sanna Passino, F. and Heard, N. A. (2020), Classification of periodic arrivals in event time data for filtering computer network traffic, Statistics and Computing 30(5), 1241-1254 (paper , code ),
Sanna Passino, F. and Heard, N. A. (2019), Modelling dynamic network evolution as a Pitman-Yor process, Foundations of Data Science 1(3), 293-306 (paper , preprint , code ).
Commentaries
Sanna Passino, F. and Heard, N. A. (2025) Sanna Passino and Heard’s contribution to the Discussion of “Statistical exploration of the Manifold Hypothesis” by Whiteley, Gray and Rubin-Delanchy, Journal of the Royal Statistical Society: Series B, to appear (paper ),
Sanna Passino, F., Adams, N. M., Cohen, E. A. K., Evangelou, M. and Heard, N. A. (2023) Statistical cybersecurity: a brief discussion of challenges, data structures and future directions, Harvard Data Science Review 5(1) (paper ).
Other preprints
Ferracci, T., Goldmann, L. T., Hinel, A., and Sanna Passino, F. (2024), Targeted synthetic data generation for tabular data via hardness characterization (arXiv , code ).
PhD thesis
Sanna Passino, F. (2020), Latent factor representations of dynamic networks with applications in cyber-security, PhD thesis, Imperial College London, London, United Kingdom (online PDF ).
