| 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 | 375 | 2015 |
| 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 | 319 | 2022 |
| 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 | 245 | 2024 |
| The Correlated Pseudo-Marginal Method G Deligiannidis, A Doucet, MK Pitt J. R. Stat. Soc. Ser. B 80 (5), 839–870, 2015 | 168 | 2015 |
| 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 | 141 | 2021 |
| Relaxing bijectivity constraints with continuously indexed normalising flows R Cornish, A Caterini, G Deligiannidis, A Doucet International conference on machine learning, 2133-2143, 2020 | 138 | 2020 |
| Controlled sequential monte carlo J Heng, AN Bishop, G Deligiannidis, A Doucet Annals of Statistics 48 (5), 2904 - 2929, 2017 | 122 | 2017 |
| Differentiable particle filtering via entropy-regularized optimal transport A Corenflos, J Thornton, G Deligiannidis, A Doucet International Conference on Machine Learning, 2100-2111, 2021 | 119 | 2021 |
| Piecewise-deterministic markov chain monte carlo P Vanetti, A Bouchard-Côté, G Deligiannidis, A Doucet arXiv preprint arXiv:1707.05296, 2017 | 113 | 2017 |
| 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 | 102 | 2023 |
| 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 | 96* | 2020 |
| Error bounds for flow matching methods J Benton, G Deligiannidis, A Doucet Transactions on Machine Learning Research, 2024 | 89 | 2024 |
| Conditional simulation using diffusion Schrödinger bridges Y Shi, V De Bortoli, G Deligiannidis, A Doucet Uncertainty in Artificial Intelligence, 1792-1802, 2022 | 81 | 2022 |
| Stable resnet S Hayou, E Clerico, B He, G Deligiannidis, A Doucet, J Rousseau International Conference on Artificial Intelligence and Statistics, 1324-1332, 2021 | 79 | 2021 |
| 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 | 68 | 2021 |
| Exponential Ergodicity of the Bouncy Particle Sampler G Deligiannidis, A Bouchard-Côté, A Doucet Annals of Statistics 47 (3), 1268-1287, 2019 | 66 | 2019 |
| From denoising diffusions to denoising markov models J Benton, Y Shi, V De Bortoli, G Deligiannidis, A Doucet Journal of the Royal Statistical Society, Series B (discussion paper) 86 (2), 2024 | 58 | 2024 |
| Particle denoising diffusion sampler A Phillips, HD Dau, MJ Hutchinson, V De Bortoli, G Deligiannidis, ... ICML 41, 2024 | 55 | 2024 |
| Unbiased Markov chain Monte Carlo for intractable target distributions L Middleton, G Deligiannidis, A Doucet, PE Jacob | 43 | 2020 |
| Large sample asymptotics of the pseudo-marginal method SM Schmon, G Deligiannidis, A Doucet, MK Pitt Biometrika 108 (1), 37-51, 2020 | 42 | 2020 |
Arnaud DoucetGoogle DeepMindVerified email at google.com
