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Valentin De Bortoli
Valentin De Bortoli
Google DeepMind, London
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
De novo design of protein structure and function with RFdiffusion
JL Watson, D Juergens, NR Bennett, BL Trippe, J Yim, HE Eisenach, ...
Nature 620 (7976), 1089-1100, 2023
4782023
Diffusion schrödinger bridge with applications to score-based generative modeling
V De Bortoli, J Thornton, J Heng, A Doucet
Advances in Neural Information Processing Systems 34, 17695-17709, 2021
3272021
Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models
JL Watson, D Juergens, NR Bennett, BL Trippe, J Yim, HE Eisenach, ...
BioRxiv, 2022.12. 09.519842, 2022
1772022
Riemannian score-based generative modelling
V De Bortoli, E Mathieu, M Hutchinson, J Thornton, YW Teh, A Doucet
Advances in Neural Information Processing Systems 35, 2406-2422, 2022
1462022
Convergence of denoising diffusion models under the manifold hypothesis
V De Bortoli
arXiv preprint arXiv:2208.05314, 2022
1212022
SE (3) diffusion model with application to protein backbone generation
J Yim, BL Trippe, V De Bortoli, E Mathieu, A Doucet, R Barzilay, ...
arXiv preprint arXiv:2302.02277, 2023
1032023
Bayesian imaging using plug & play priors: when langevin meets tweedie
R Laumont, VD Bortoli, A Almansa, J Delon, A Durmus, M Pereyra
SIAM Journal on Imaging Sciences 15 (2), 701-737, 2022
972022
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
862022
Linear convergence bounds for diffusion models via stochastic localization
J Benton, V De Bortoli, A Doucet, G Deligiannidis
arXiv preprint arXiv:2308.03686, 2023
712023
Diffusion Schrödinger bridge matching
Y Shi, V De Bortoli, A Campbell, A Doucet
Advances in Neural Information Processing Systems 36, 2024
612024
Maximum likelihood estimation of regularization parameters in high-dimensional inverse problems: An empirical bayesian approach part i: Methodology and experiments
AF Vidal, V De Bortoli, M Pereyra, A Durmus
SIAM Journal on Imaging Sciences 13 (4), 1945-1989, 2020
542020
Conditional simulation using diffusion Schrödinger bridges
Y Shi, V De Bortoli, G Deligiannidis, A Doucet
Uncertainty in Artificial Intelligence, 1792-1802, 2022
462022
Wavelet score-based generative modeling
F Guth, S Coste, V De Bortoli, S Mallat
Advances in neural information processing systems 35, 478-491, 2022
452022
Efficient stochastic optimisation by unadjusted Langevin Monte Carlo: Application to maximum marginal likelihood and empirical Bayesian estimation
V De Bortoli, A Durmus, M Pereyra, AF Vidal
Statistics and Computing 31, 1-18, 2021
402021
Approximate Bayesian computation with the sliced-Wasserstein distance
K Nadjahi, V De Bortoli, A Durmus, R Badeau, U Şimşekli
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
382020
Can push-forward generative models fit multimodal distributions?
A Salmona, V De Bortoli, J Delon, A Desolneux
Advances in Neural Information Processing Systems 35, 10766-10779, 2022
362022
Convergence rates and approximation results for SGD and its continuous-time counterpart
X Fontaine, V De Bortoli, A Durmus
Conference on Learning Theory, 1965-2058, 2021
33*2021
Quantitative propagation of chaos for SGD in wide neural networks
V De Bortoli, A Durmus, X Fontaine, U Simsekli
Advances in Neural Information Processing Systems 33, 278-288, 2020
322020
Simulating diffusion bridges with score matching
J Heng, V De Bortoli, A Doucet, J Thornton
arXiv preprint arXiv:2111.07243, 2021
312021
Maximum likelihood estimation of regularization parameters in high-dimensional inverse problems: an empirical Bayesian approach. Part II: Theoretical analysis
V De Bortoli, A Durmus, M Pereyra, AF Vidal
SIAM Journal on Imaging Sciences 13 (4), 1990-2028, 2020
292020
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Articles 1–20