Working papers
On robust Bayesian causal inference, with Nikos DemirisÂ
The heterogeneous causal effects of the EU's Cohesion Fund, with Ilias Kostarakos, Christos Mylonakis and Petros Varthalitis
Gaussian Invariant Markov Chain Monte Carlo, with Michalis Titsias, Petros Dellaportas and Liu Siran
A computationally efficient framework for realistic epidemic modelling through Gaussian Markov random fields, with Paul Birrell and Daniela De Angelis
Targeting Coordinated VAT Fraud: A Data-Driven Framework for Risk-Based Enforcement, with Konstantinos Bourazas and Christos Kotsogiannis
Tax Fraud Detection via Bayesian PU Learning with Gaussian Processes and Multi-Layer Networks, with Konstantinos Bourazas, Petros Dellaportas and Konstantinos Kalogeropoulos
Buyers as Auditors in the Fuel Market: Evidence from Administrative Data, with Christos Kotsogiannis and Christos Mylonakis
Published Papers (Selected)
A network approach to detect Value Added Tax fraud, with P. Dellaportas, S. Gyoshev, C. Kotsogiannis, S. Olhede, T. Pavkov, Journal of the Royal Statistical Society Series A: Statistics in Society, 2025, DOI: https://doi.org/10.1093/jrsssa/qnaf205
A machine learning approach to construct quarterly data on intangible investment for Eurozone, with P. Varthalitis, Economics Letters, 2023, DOI: https://doi.org/10.1016/j.econlet.2023.111307
Variance reduction for Metropolis-Hastings samplers, with P. Dellaportas and M. Titsias, Statistics and Computing, 2023, DOI: https://doi.org/10.1007/s11222-022-10183-2
A Bayesian multivariate factor analysis model for causal inference using time-series observational data on mixed outcomes, with P. Samartsidis, SR Seaman, A. Harrison, GJ Hughes, C. Rawlinson, C. Anderson, A. Charlett, I. Oliver, D. De Angelis, Biostatistics, 2023, DOI: https://doi.org/10.1093/biostatistics/kxad030
Bayesian prediction of jumps in large panels of time series data, with P. Dellaportas and O. Papaspiliopoulos, Bayesian Analysis, 2022, DOI: 10.1214/21-BA1268
Bayesian variable selection for Gaussian copula regression models, with L. Bottolo, Journal of Computational and Graphical Statistics, 2021, DOI: https://doi.org/10.1080/10618600.2020.1840997
Bayesian forecasting of mortality rates, with P. Dellaportas and J. Forster, Journal of the Royal Statistical Society Series A: Statistics in Society, 2019, DOI: https://doi.org/10.1111/rssa.12422