Petros Dellaportas

Latest

• Learning variational autoencoders via MCMC speed measures
• Bayesian Tensor Factorisations for Time Series of Counts
• Reservoir computing for macroeconomic forecasting with mixed frequency data
• Bayesian online change point detection with Hilbert space approximate Student-t process
• Doubly-online changepoint detection for monitoring health status during sports activities
• Flexible marked spatio-temporal point processes with applications to event sequences from association football
• Inference for partially observed Riemannian Ornstein-Uhlenbeck diffusions of covariance matrices
• Missing data patterns in runners’ careers: do they matter?
• Scalable and Interpretable Marked Point Processes
• Sparse Spectral Bayesian Permanental Process with Generalized Kernel
• Variance Reduction for Metropolis-Hastings Samplers
• Bayesian prediction of jumps in large panels of time series data
• How Good are Low-Rank Approximations in Gaussian Process Regression?
• Detecting anomalies in heterogeneous population-scale VAT networks
• Entropy-based adaptive Hamiltonian Monte Carlo
• Large scale multi-label learning using Gaussian processes
• Scalable inference for a full multivariate stochastic volatility model
• Interview with Professor Adrian FM Smith
• Sample size determination for risk-based tax auditing
• Bayesian forecasting of mortality rates by using latent Gaussian models
• Copula-like Variational Inference
• Efficient sequential Monte Carlo algorithms for integrated population models
• Gradient-based adaptive Markov chain Monte Carlo
• Importance sampling from posterior distributions using copula-like approximations
• Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers
• Scalable inference for a full multivariate stochastic volatility model
• Sovereign risk zones in Europe during and after the debt crisis
• A Bayesian Approach for Analysis of Whole-Genome Bisulfite Sequencing Data Identifies Disease-Associated Changes in DNA Methylation
• Bayesian Hierarchical Mixture Models
• Volatility prediction based on scheduled macroeconomic announcements
• WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools
• Arbitrage-free prediction of the implied volatility smile
• Communication impacting financial markets
• Museum factors affecting the ageing process of organic materials: review on experimental designs and the INVENVORG project as a pilot study
• An MCMC model search algorithm for regression problems
• Bayesian Theory and Applications
• Cholesky-GARCH models with applications to finance
• Conditional symmetry models for three-way contingency tables
• Contagion determination via copula and volatility threshold models
• Control variates for estimation based on reversible Markov chain Monte Carlo samplers
• Joint specification of model space and parameter space prior distributions
• A novel reversible jump algorithm for generalized linear models
• Forecasting with non-homogeneous hidden Markov models
• Likelihood-based inference for correlated diffusions
• Inference for stochastic volatility models using time change transformations
• Bayesian clustering for row effects models
• Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models
• Flexible threshold models for modelling interest rate volatility
• Modelling volatility asymmetries: a Bayesian analysis of a class of tree structured multivariate GARCH models
• Bayesian model selection for partially observed diffusion models
• Multivariate mixtures of normals with unknown number of components
• Bayesian analysis of the unobserved arch model
• Model determination for categorical data with factor level merging
• Bayesian inference for non-Gaussian Ornstein--Uhlenbeck stochastic volatility processes
• Periodic Markov switching autoregressive models for Bayesian analysis and forecasting of air pollution
• Quantification of automobile insurance liability: a Bayesian failure time approach
• A full-factor multivariate GARCH model
• An introduction to MCMC
• Assessment of Athens's metro passenger behaviour via a multiranked probit model
• Bayesian analysis of extreme values by mixture modeling
• Bayesian inference for nondecomposable graphical Gaussian models
• Bayesian variable and link determination for generalised linear models
• Inference for some multivariate ARCH and GARCH models
• Bayesian modelling of outstanding liabilities incorporating claim count uncertainty
• On Bayesian model and variable selection using MCMC
• A simulation approach to hierarchical models
• A simulation approach to nonparametric empirical Bayes analysis
• An application of three bivariate time-varying volatility models
• Bayesian analysis of correlated proportions
• Bayesian analysis of mortality data
• Wind speed prediction in a complex terrain
• An approach to multidimensional item response modeling
• Bayesian variable selection using the Gibbs sampler
• Full Bayesian inference for GARCH and EGARCH models
• Stochastic search variable selection for log-linear models
• A Markov chain Monte Carlo convergence diagnostic using subsampling
• Fatigue loading parameter identification of a wind turbine operating in complex terrain
• Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models
• Prediction of wind speed and direction at a potential site
• Bayesian classification of neolithic tools
• An approach to diagnosing total variation convergence of MCMC algorithms
• The role of embedded integration rules in Bayesian statistics
• Bayesian analysis of errors-in-variables regression models
• Random variate transformations in the Gibbs sampler: Issues of efficiency and convergence
• Bayesian inference for generalized linear and proportional hazards models via Gibbs sampling
• Numerical prediction for the two-parameter Weibull distribution
• Positive embedded integration in Bayesian analysis