|Themes||Computational Statistics, General Theory and Methodology, Multivariate and High Dimensional Data,|
Before taking up his current post at UCL in October 2015, Petros Dellaportas was professor at the Athens University of Economics and Business. He has a Phd in Statistics jointly from the University of Plymouth and University of Sheffield, an MSc in Statistics from the University of Sheffield and an undergraduate degree in Mathematics from the University of Athens. He is a co-editor of Bayesian Analysis and has served as an associate editor in Biometrika, Electronic journal of statistics, Statistical modelling, Journal of the royal statistical society series D.
Machine learning, Bayesian theory and applications, financial modelling.
- Hirt M., Titsias M. and Dellaportas P. (2021). Gradient-based adaptative HMC. Advances in Neural Information Processing Systems (NeurIPS).
- Hirt M., Dellaportas P, Durmus A.(2019). Copula-like Variational Inference. Advances in Neural Information Processing Systems (NeurIPS).
- Titsias M. and Dellaportas P. (2019). Gradient-based adaptive Markov chain Monte Carlo. Advances in Neural Information Processing Systems (NeurIPS).
- Dellaportas P. and Kontoyiannis I. (2012). Control variates for reversible MCMC Samplers. Journal of the Royal Statistical Society, Series B. 74, 1, 133-161.
- Papathomas M., Dellaportas P. And Vasdekis V.G.S. (2011). A novel reversible jump algorithm for generalized linear models. Biometrika, 98, 231-236.
- Kalogeropoulos K., Roberts G.O. and Dellaportas P. (2010). Inference for stochastic volatility models using time change transformations Annals of Statistics, 38, 2, 784-807.
- Dellaportas P., Friel N. and Roberts G.O. (2006). Bayesian model selection for partially observed diffusion models. Biometrika.93,4,809-825.
- Roberts G.O., Papaspiliopoulos O. and Dellaportas P (2004). Bayesian inference for Non-Gaussian Ornstein-Uhlenbeck Stochastic Volatility processes. Journal of the Royal Statistical Society, Series B, 66, 369-393.
- Dellaportas P. and Tarantola C. (2005). Categorical data squashing by combining factor levels. Journal of the Royal Statistical Society, Series B, 67,269-283.
- Dellaportas P and Forster J J (1999) Markov chain Monte Carlo Model Determination for Hierarchical and Graphical Log-linear models. Biometrika, 86, 615-633.