25 citations · 55 across the 8 of their papers we have counts for
8 papers
AI Receptivity or AI Adoption Breadth? A Tool-Specific Reanalysis of the Lower-Literacy/Higher-Usage Link
Hristo Inouzhe
Recent evidence reported by Tully, Longoni, and Appel (2025) suggests that lower artificial intelligence (AI) literacy predicts greater receptivity toward AI. We revisit this claim…
Adaptive tuning of Hamiltonian Monte Carlo methods
Elena Akhmatskaya, Lorenzo Nagar, Jose Antonio Carrillo +4
With the recently increased interest in probabilistic models, the efficiency of an underlying sampler becomes a crucial consideration. Hamiltonian Monte Carlo (HMC) is one popular…
A study on group fairness in healthcare outcomes for nursing home residents during the COVID-19 pandemic in the Basque Country
Hristo Inouzhe, Irantzu Barrio, Paula Gordaliza +3
We explore the effect of nursing home status on healthcare outcomes such as hospitalisation, mortality and in-hospital mortality during the COVID-19 pandemic. Some claim that in sp…
Compartmental Disease Models with Time-Varying Transmission Rates: A Bayesian Generalized Hamiltonian Monte Carlo framework with Applications to COVID-19
Hristo Inouzhe, María Xosé Rodríguez-Álvarez, Lorenzo Nagar +1
Epidemic transmission is shaped by changing behaviour, interventions, and unobserved factors, while incidence data are noisy and incomplete. We develop a Bayesian statistical-mecha…
optimalFlow: Optimal-transport approach to flow cytometry gating and population matching
Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes +2
Data obtained from Flow Cytometry present pronounced variability due to biological and technical reasons. Biological variability is a well-known phenomenon produced by measurements…
Attraction-Repulsion clustering with applications to fairness
Eustasio del Barrio, Hristo Inouzhe, Jean-Michel Loubes
We consider the problem of diversity enhancing clustering, i.e, developing clustering methods which produce clusters that favour diversity with respect to a set of protected attrib…
On approximate validation of models: A Kolmogorov-Smirnov based approach
Eustasio del Barrio, Hristo Inouzhe, Carlos Matrán
Classical tests of fit typically reject a model for large enough real data samples. In contrast, often in statistical practice a model offers a good description of the data even th…
Box-constrained monotone -approximations to Lipschitz regularizations, with applications to robust testing
Eustasio del Barrio, Hristo Inouzhe, Carlos Matrán
Tests of fit to exact models in statistical analysis often lead to rejections even when the model is a useful approximate description of the random generator of the data. Among pos…