Petros Dellaportas

According to our database, Petros Dellaportas authored at least 25 papers between 1996 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Learning variational autoencoders via MCMC speed measures.

Marcel Hirt, Vasileios Kreouzis, Petros Dellaportas

Stat. Comput., October, 2024

Bayesian tensor factorisations for time series of counts.

Zhongzhen Wang, Petros Dellaportas, Ioannis Kosmidis

Mach. Learn., June, 2024

Can independent Metropolis beat crude Monte Carlo?

Siran Liu, Petros Dellaportas, Michalis K. Titsias

CoRR, 2024

Probabilistic Multi-Layer Perceptrons for Wind Farm Condition Monitoring.

Filippo Fiocchi, Domna Ladopoulou, Petros Dellaportas

CoRR, 2024

2023

Variance reduction for Metropolis-Hastings samplers.

Angelos Alexopoulos, Petros Dellaportas, Michalis K. Titsias

Stat. Comput., 2023

Bayesian online change point detection with Hilbert space approximate Student-t process.

Jeremy Sellier, Petros Dellaportas

Proceedings of the International Conference on Machine Learning, 2023

Sparse Spectral Bayesian Permanental Process with Generalized Kernel.

Jeremy Sellier, Petros Dellaportas

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Scalable marked point processes for exchangeable and non-exchangeable event sequences.

Aristeidis Panos, Ioannis Kosmidis, Petros Dellaportas

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

How Good Are Low-Rank Approximations in Gaussian Process Regression?

Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Large scale multi-label learning using Gaussian processes.

Aristeidis Panos, Petros Dellaportas, Michalis K. Titsias

Mach. Learn., 2021

Scalable and Interpretable Marked Point Processes.

Aristeidis Panos, Ioannis Kosmidis, Petros Dellaportas

CoRR, 2021

Entropy-based adaptive Hamiltonian Monte Carlo.

Marcel Hirt, Michalis K. Titsias, Petros Dellaportas

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Faster Gaussian Processes via Deep Embeddings.

Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos

CoRR, 2020

2019

Gradient-based Adaptive Markov Chain Monte Carlo.

Michalis K. Titsias, Petros Dellaportas

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Copula-like Variational Inference.

Marcel Hirt, Petros Dellaportas, Alain Durmus

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers.

Marcel Hirt, Petros Dellaportas

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Fully Scalable Gaussian Processes using Subspace Inducing Inputs.

Aristeidis Panos, Petros Dellaportas, Michalis K. Titsias

CoRR, 2018

2015

WGBSSuite: simulating whole-genome bisulphite sequencing data and benchmarking differential DNA methylation analysis tools.

Owen J. L. Rackham, Petros Dellaportas, Enrico Petretto, Leonardo Bottolo

Bioinform., 2015

2012

Cholesky-GARCH models with applications to finance.

Petros Dellaportas, Mohsen Pourahmadi

Stat. Comput., 2012

2011

Forecasting with non-homogeneous hidden Markov models.

Loukia Meligkotsidou, Petros Dellaportas

Stat. Comput., 2011

2008

Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models.

D. Giannikis, Ioannis D. Vrontos, Petros Dellaportas

Comput. Stat. Data Anal., 2008

2006

Multivariate mixtures of normals with unknown number of components.

Petros Dellaportas, Ioulia Papageorgiou

Stat. Comput., 2006

2005

Bayesian analysis of the unobserved ARCH model.

Stefanos G. Giakoumatos, Petros Dellaportas, Dimitris Nicolas Politis

Stat. Comput., 2005

2002

On Bayesian model and variable selection using MCMC.

Petros Dellaportas, Jonathan J. Forster, Ioannis Ntzoufras

Stat. Comput., 2002

1996

The role of embedded integration rules in Bayesian statistics.

Ronald Cools, Petros Dellaportas

Stat. Comput., 1996