Sanna Passino, F., Mantziou, A., Ghani, D., Thiede, P., Bevington, R., and Heard, N. A. (2023), Nested Dirichlet models for unsupervised attack pattern detection in honeypot data (arXiv , code ).
Published
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 - WWW ‘21 (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., 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 ).
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 ).
