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Vincent Dutordoir
Vincent Dutordoir
Google DeepMind
Verified email at cam.ac.uk - Homepage
Title
Cited by
Cited by
Year
A framework for interdomain and multioutput Gaussian processes
M Van der Wilk, V Dutordoir, ST John, A Artemev, V Adam, J Hensman
arXiv preprint arXiv:2003.01115, 2020
962020
Sparse Gaussian processes with spherical harmonic features
V Dutordoir, N Durrande, J Hensman
International Conference on Machine Learning, 2793-2802, 2020
602020
Gaussian process conditional density estimation
V Dutordoir, H Salimbeni, J Hensman, M Deisenroth
Advances in Neural Information Processing Systems, NeurIPS, 2385-2395, 2018
602018
Deep Gaussian Processes with Importance-Weighted Variational Inference
H Salimbeni, V Dutordoir, J Hensman, MP Deisenroth
International Conference on Machine Learning, ICML, 2019
562019
A tutorial on sparse Gaussian processes and variational inference
F Leibfried, V Dutordoir, ST John, N Durrande
arXiv preprint arXiv:2012.13962, 2020
432020
Bayesian image classification with deep convolutional Gaussian processes
V Dutordoir, M Wilk, A Artemev, J Hensman
International Conference on Artificial Intelligence and Statistics, 1529-1539, 2020
43*2020
Scalable Thompson sampling using sparse Gaussian process models
S Vakili, H Moss, A Artemev, V Dutordoir, V Picheny
Advances in neural information processing systems 34, 5631-5643, 2021
352021
Deep neural networks as point estimates for deep Gaussian processes
V Dutordoir, J Hensman, M van der Wilk, CH Ek, Z Ghahramani, ...
Advances in Neural Information Processing Systems 34, 9443-9455, 2021
312021
GPflux: a library for deep gaussian processes
V Dutordoir, H Salimbeni, E Hambro, J McLeod, F Leibfried, A Artemev, ...
arXiv preprint arXiv:2104.05674, 2021
262021
Neural diffusion processes
V Dutordoir, A Saul, Z Ghahramani, F Simpson
International Conference on Machine Learning, 8990-9012, 2023
232023
Deep gaussian process metamodeling of sequentially sampled non-stationary response surfaces
V Dutordoir, N Knudde, J van der Herten, I Couckuyt, T Dhaene
Winter Simulation Conference, 134, 2017
72017
Memory-based meta-learning on non-stationary distributions
T Genewein, G Delétang, A Ruoss, LK Wenliang, E Catt, V Dutordoir, ...
International conference on machine learning, 11173-11195, 2023
52023
Geometric neural diffusion processes
E Mathieu, V Dutordoir, M Hutchinson, V De Bortoli, YW Teh, R Turner
Advances in Neural Information Processing Systems 36, 2024
42024
Hierarchical gaussian process models for improved metamodeling
N Knudde, V Dutordoir, JVD Herten, I Couckuyt, T Dhaene
ACM Transactions on Modeling and Computer Simulation (TOMACS) 30 (4), 1-17, 2020
42020
Automatic tuning of stochastic gradient descent with Bayesian optimisation
V Picheny, V Dutordoir, A Artemev, N Durrande
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021
22021
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design
K Didi, F Vargas, SV Mathis, V Dutordoir, E Mathieu, UJ Komorowska, ...
arXiv preprint arXiv:2312.09236, 2023
12023
Spherical inducing features for orthogonally-decoupled gaussian processes
LC Tiao, V Dutordoir, V Picheny
International Conference on Machine Learning, 34143-34160, 2023
12023
Efficient computational inference using gaussian processes
V Dutordoir, J Hensman, N Durrande
US Patent 11,027,743, 2021
12021
Non-Stationary Surrogate Modeling with Deep Gaussian.”
V Dutordoir
12017
Efficient computational inference using Gaussian processes
V Dutordoir, J Hensman, N Durrande
US Patent 11,673,560, 2023
2023
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