39 citations · 140 across the 29 of their papers we have counts for
7 papers · 1 filter
From Past to Future: Digital Methods Towards Artefact Analysis
Andrew Harris, Andrea Cremaschi, Tse Siang Lim +2
Over the past two decades, Digital Humanities has transformed the landscape of humanities and social sciences, enabling advanced computational analysis and interpretation of extens…
Bayesian modelling of response to therapy and drug-sensitivity in acute lymphoblastic leukemia
Andrea Cremaschi, Wenjian Yang, Maria De Iorio +3
Acute lymphoblastic leukemia (ALL) is a heterogeneous hematologic malignancy involving the abnormal proliferation of immature lymphocytes, accounting for most pediatric cancer case…
Graph of Graphs: From Nodes to Supernodes in Graphical Models
Maria De Iorio, Willem van den Boom, Alexandros Beskos +2
High-dimensional data analysis typically focuses on low-dimensional structure, often to aid interpretation and computational efficiency. Graphical models provide a powerful methodo…
The Multivariate Bernoulli detector: Change point estimation in discrete survival analysis
Willem van den Boom, Maria De Iorio, Fang Qian +1
Time-to-event data are often recorded on a discrete scale with multiple, competing risks as potential causes for the event. In this context, application of continuous survival anal…
Conditional partial exchangeability: a probabilistic framework for multi-view clustering
Beatrice Franzolini, Maria De Iorio, Johan Eriksson
Standard clustering techniques assume a common configuration for all features in a dataset. However, when dealing with multi-view or longitudinal data, the clusters' number, freque…
Repulsion, Chaos and Equilibrium in Mixture Models
Andrea Cremaschi, Timothy M. Wertz, Maria De Iorio
Mixture models are commonly used in applications with heterogeneity and overdispersion in the population, as they allow the identification of subpopulations. In the Bayesian framew…
Annealing Double-Head: An Architecture for Online Calibration of Deep Neural Networks
Erdong Guo, David Draper, Maria De Iorio
Model calibration, which is concerned with how frequently the model predicts correctly, not only plays a vital part in statistical model design, but also has substantial practical…