Professor George Deligiannidis

Associate Professor of Statistics

Biographical Sketch

I studied Mathematics (MMath) at the University of Warwick and Financial Mathematics (MSc) at Heriot-Watt University and the University of Edinburgh. After obtaining my PhD from the School of Mathematical Sciences of the University of Nottingham under the supervision of Sergey Utev and Huiling Le, I moved to the Department of Mathematics of the University of Leicester as a Teaching Assistant/Fellow. In 2012 I moved to the Department of Statistics of the University of Oxford as Departmental Lecturer. I stayed in Oxford until September 2016 when I moved to the Department of Mathematics of King’s College London as Lecturer in Statistics. I moved back to the University of Oxford in December 2017 as Associate Professor of Statistics.

News

I recently received a New Investigator Award from EPSRC. I will be hiring a postdoc for three years to work on this project. If interested, you can apply here .

Research Interests

I work in the intersection of probability and statistics to analyse random processes and objects, especially those arising from algorithms used in computational statistics and machine learning. I have worked extensively on the theory and methodology of sampling methods, especially Markov Chain Monte Carlo. I have also worked on random walks on lattices and groups.
At the moment I am particularly interested in the interplay between sampling, optimization and machine learning.

Publications

Personal website
Corenflos, A., Thornton, J., Deligiannidis, G. and Doucet, A. (2021) “Differentiable particle filtering via entropy-regularized optimal transport”, in. Journal of Machine Learning Research, pp. 2100–2111.
Clerico, E., Deligiannidis, G. and Doucet, A. (2021) “Wide stochastic networks: Gaussian limit and PAC-Bayesian training”, arXiv.
Camuto, A., Deligiannidis, G., Erdogdu, M., Gürbüzbalaban, M., Şimşekli, U. and Zhu, L. (2021) “Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms”, arXiv.
Hayou, S., Clerico, E., He, B., Deligiannidis, G., Doucet, A. and Rousseau, J. (2021) “Stable ResNet”, in Proceedings of The 24th International Conference on Artificial Intelligence and Statistics. Journal of Machine Learning Research, pp. 1324–1332.
Camuto, A., Deligiannidis, G., Erdogdu, M., Gürbüzbalaban, M., Şimşekli, U. and Zhu, L. (2021) “Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms”, in Advances in Neural Information Processing Systems, pp. 18774–18788.
Deligiannidis, G., Gouëzel, S. and Kosloff, Z. (2021) “The boundary of the range of a random walk and the følner property<sup>*</sup>”, Electronic Journal of Probability, 26.
Corenflos, A., Thornton, J., Deligiannidis, G. and Doucet, A. (2021) “Differentiable Particle Filtering via Entropy-Regularized Optimal Transport”, in INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139.
Faizi, F., Buigues, P., Deligiannidis, G. and Rosta, E. (2020) “Simulated tempering with irreversible Gibbs sampling techniques.”, The Journal of chemical physics, 153(21), p. 214111.
Heng, J., Bishop, A., Deligiannidis, G. and Doucet, A. (2020) “Controlled sequential Monte Carlo”, Annals of Statistics, 48(5), pp. 2904–2929.
Faizi, F., Buigues, P., Deligiannidis, G. and Rosta, E. (2020) “Simulated tempering with irreversible Gibbs sampling techniques”, arXiv.

Publications

Corenflos, A., Thornton, J., Deligiannidis, G. and Doucet, A. (2021) “Differentiable particle filtering via entropy-regularized optimal transport”, in. Journal of Machine Learning Research, pp. 2100–2111.
Clerico, E., Deligiannidis, G. and Doucet, A. (2021) “Wide stochastic networks: Gaussian limit and PAC-Bayesian training”, arXiv.
Camuto, A., Deligiannidis, G., Erdogdu, M., Gürbüzbalaban, M., Şimşekli, U. and Zhu, L. (2021) “Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms”, arXiv.
Hayou, S., Clerico, E., He, B., Deligiannidis, G., Doucet, A. and Rousseau, J. (2021) “Stable ResNet”, in Proceedings of The 24th International Conference on Artificial Intelligence and Statistics. Journal of Machine Learning Research, pp. 1324–1332.
Camuto, A., Deligiannidis, G., Erdogdu, M., Gürbüzbalaban, M., Şimşekli, U. and Zhu, L. (2021) “Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms”, in Advances in Neural Information Processing Systems, pp. 18774–18788.
Deligiannidis, G., Gouëzel, S. and Kosloff, Z. (2021) “The boundary of the range of a random walk and the følner property<sup>*</sup>”, Electronic Journal of Probability, 26.
Corenflos, A., Thornton, J., Deligiannidis, G. and Doucet, A. (2021) “Differentiable Particle Filtering via Entropy-Regularized Optimal Transport”, in INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139.
Faizi, F., Buigues, P., Deligiannidis, G. and Rosta, E. (2020) “Simulated tempering with irreversible Gibbs sampling techniques.”, The Journal of chemical physics, 153(21), p. 214111.
Heng, J., Bishop, A., Deligiannidis, G. and Doucet, A. (2020) “Controlled sequential Monte Carlo”, Annals of Statistics, 48(5), pp. 2904–2929.
Faizi, F., Buigues, P., Deligiannidis, G. and Rosta, E. (2020) “Simulated tempering with irreversible Gibbs sampling techniques”, arXiv.

Contact Details

College Affiliation: Hugh Price Fellow at Jesus College

Email: deligian@stats.ox.ac.uk

Telephone: +44(0)1865 282851

Office number: 1.05

Graduate Students

Joe Benton

Amitis Shidani

Eugenio Clerico

Chris Williams

Angus Philips

Guneet Dhillon

James Thornton 

Research Groups

Computational Statistics and Machine Learning

Statistical Theory and Methodology