Talk – Just back from Bertinoro (Italy) - Always great participating in the Working Group on Model-based Clustering, where I have presented our work with Iuliia Promskaia and Adrian O’Hagan on clustering networks with compositional edges.
New paper! – A machine learning approach to predict in vivo skin growth published in Scientific Reports! Work led by Matt Nagle, with Aisling Ní Annaidh, Hannah Conroy Broderick, and Adrian Buganza Tepole. Available online here.
New preprint! – Promskaia I., O’Hagan A., Fop M. (2024)
A Dirichlet stochastic block model for composition-weighted networks. arXiv
New paper! – A Gaussian process approach for rapid evaluation of skin tension from work led by Matt Nagle, with Aisling Ní Annaidh and Hannah Conroy Broderick, published in Acta Biomaterialia! Available online here.
New paper! – Variational inference for the latent shrinkage position model with Xian Yao Gwee and Claire Gormley now available on Stat! See it here.
Talk - A pleasure to participate in the 4th Iinternational Workshop on Spectroscopy and Chemometrics, where I gave an overview of clustering methods that can be used to cluster high-dimensional spectroscopy data. It was great to network with experts in the field and learn about many interesting applications and problems in spectroscopy!
New preprint! – Pacheco Menezes T., Murphy T. B., Fop M. (2024)
Hausdorff distance-based record linkage for improved matching of households and individuals in different databases. arXiv
I’ve been appointed Associated Editor of the Journal of Data Science, Statistics, and Visualisation, an open access journal of the International Association for Statistical Computing (IASC).
The journal welcomes contributions of interest to a wide scientific audience and at the intersection of machine learning, statistics, and data visualization. Looking forward to contributing to the activities of this journal!
New preprint! – Babu G., Gowen A., Fop M., Gormley I. C. (2024)
A consensus-constrained parsimonious Gaussian mixture model for clustering hyperspectral images. arXiv
New preprint! – Gwee X. Y., Gormley I. C., Fop M. (2023)
Model-based clustering for network data via a latent shrinkage position cluster model. arXiv
New paper! – A latent shrinkage position model for binary and count network data with Xian Yao Gwee and Claire Gormley to appear in the journal Bayesian Analysis! Preprint here and code here.
Talk – Great to visit Carnegie Mellon University in Pittsburgh (USA) to present our work with Xian Yao Gwee and Claire Gormley on clustering and dimension reduction for network data at the Working Group in Model-based Clustering!
They really love pickles in that city and pickle beer is really a thing!
New preprint! – Cappozzo A., Casa A., Fop M. (2023)
Sparse model-based clustering of three-way data via lasso-type penalties. arXiv
Talk – Back to Sicily again! Thanks Roberto di Mari for inviting me at the University of Catania to present our joint work with Riccardo Rastelli on clustering time-dependent network interaction data (paper here).
New preprint! – Gwee X. Y., Gormley I. C., Fop M. (2022)
A latent shrinkage position model for binary and count network data. arXiv | Code
Talk – Just back from Sicily where I participated in the 6th Workshop on Models and Learning in Clustering and Classification (MBC2) – Presented some work in progress on clustering mixed-type data …stay tuned!
Lecture – A pleasure to give a class on programming with R to the new cohort of the SFI CRT Foundations of Data Science students!
Talk – Attended the 17th conference of the International Federation of Classification Societies, where I’ve been invited to present our work in the invited session on Dimension reduction organized by Cinzia Viroli.
Talk – Back again to the Working Group in Model-based Clustering, albeit on Zoom, to present our research on Model-based clustering of mixed-type data via mixtures of mixed graphical models.