Stebėti
George Deligiannidis
George Deligiannidis
Professor of Statistics, University of Oxford
Patvirtintas el. paštas stats.ox.ac.uk - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator
A Doucet, MK Pitt, G Deligiannidis, R Kohn
Biometrika 102 (2), 295-313, 2015
3552015
The Correlated Pseudo-Marginal Method
G Deligiannidis, A Doucet, MK Pitt
J. R. Stat. Soc. Ser. B 80 (5), 839–870, 2015
1622015
NEARLY -LINEAR CONVERGENCE BOUNDS FOR DIFFUSION MODELS VIA STOCHASTIC LOCALIZATION
J Benton, V De Bortoli, A Doucet, G Deligiannidis
The Twelfth International Conference on Learning Representations, 2024
117*2024
A continuous time framework for discrete denoising models
A Campbell, J Benton, V De Bortoli, T Rainforth, G Deligiannidis, ...
Advances in Neural Information Processing Systems 35, 28266-28279, 2022
1172022
Relaxing bijectivity constraints with continuously indexed normalising flows
R Cornish, A Caterini, G Deligiannidis, A Doucet
International conference on machine learning, 2133-2143, 2020
1172020
Piecewise-deterministic markov chain monte carlo
P Vanetti, A Bouchard-Côté, G Deligiannidis, A Doucet
arXiv preprint arXiv:1707.05296, 2017
1042017
Controlled sequential monte carlo
J Heng, AN Bishop, G Deligiannidis, A Doucet
Annals of Statistics 48 (5), 2904 - 2929, 2017
982017
Differentiable particle filtering via entropy-regularized optimal transport
A Corenflos, J Thornton, G Deligiannidis, A Doucet
International Conference on Machine Learning, 2100-2111, 2021
912021
Non-reversible parallel tempering: a scalable highly parallel MCMC scheme
S Syed, A Bouchard-Côté, G Deligiannidis, A Doucet
Journal of the Royal Statistical Society, Series B 84 (2), 321-350, 2021
852021
Hausdorff dimension, heavy tails, and generalization in neural networks
U Simsekli, O Sener, G Deligiannidis, MA Erdogdu
Advances in Neural Information Processing Systems 33, 5138-5151, 2020
66*2020
Randomized Hamiltonian Monte Carlo as scaling limit of the bouncy particle sampler and dimension-free convergence rates
G Deligiannidis, D Paulin, A Bouchard-Côté, A Doucet
Annals of Applied Probability 31 (6), 2612-2662, 2021
642021
Stable resnet
S Hayou, E Clerico, B He, G Deligiannidis, A Doucet, J Rousseau
International Conference on Artificial Intelligence and Statistics, 1324-1332, 2021
622021
Exponential Ergodicity of the Bouncy Particle Sampler
G Deligiannidis, A Bouchard-Côté, A Doucet
Annals of Statistics 47 (3), 1268-1287, 2019
592019
Conditional simulation using diffusion Schrödinger bridges
Y Shi, V De Bortoli, G Deligiannidis, A Doucet
Uncertainty in Artificial Intelligence, 1792-1802, 2022
552022
A unified framework for U-Net design and analysis
C Williams, F Falck, G Deligiannidis, CC Holmes, A Doucet, S Syed
Advances in Neural Information Processing Systems 36, 27745-27782, 2023
442023
Error bounds for flow matching methods
J Benton, G Deligiannidis, A Doucet
Transactions on Machine Learning Research, 2024
422024
Large sample asymptotics of the pseudo-marginal method
SM Schmon, G Deligiannidis, A Doucet, MK Pitt
Biometrika 108 (1), 37-51, 2020
392020
Unbiased Markov chain Monte Carlo for intractable target distributions
L Middleton, G Deligiannidis, A Doucet, PE Jacob
372020
Fractal structure and generalization properties of stochastic optimization algorithms
A Camuto, G Deligiannidis, MA Erdogdu, M Gurbuzbalaban, U Simsekli, ...
Advances in Neural Information Processing Systems 34, 18774-18788, 2021
272021
Scalable Metropolis-Hastings for exact Bayesian inference with large datasets
R Cornish, P Vanetti, A Bouchard-Côté, G Deligiannidis, A Doucet
ICML, 2019
272019
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Straipsniai 1–20