Vincent Dutordoir

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 29

Top Topics

Gaussian Process

Diffusion Processes

Top Venues

Publications

Peter Mostowsky, Vincent Dutordoir, Iskander Azangulov, Noémie Jaquier, Michael John Hutchinson, Aditya Ravuri, Leonel Rozo, Alexander Terenin, Viacheslav Borovitskiy
The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs. CoRR (2024)
Alexander Denker, Francisco Vargas, Shreyas Padhy, Kieran Didi, Simon V. Mathis, Vincent Dutordoir, Riccardo Barbano, Emile Mathieu, Urszula Julia Komorowska, Pietro Lio
DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform. CoRR (2024)
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
Memory-Based Meta-Learning on Non-Stationary Distributions. CoRR (2023)
Kieran Didi, Francisco Vargas, Simon V. Mathis, Vincent Dutordoir, Emile Mathieu, Urszula J. Komorowska, Pietro Lio
A framework for conditional diffusion modelling with applications in motif scaffolding for protein design. CoRR (2023)
Emile Mathieu, Vincent Dutordoir, Michael J. Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard E. Turner
Geometric Neural Diffusion Processes. CoRR (2023)
Emile Mathieu, Vincent Dutordoir, Michael Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard E. Turner
Geometric Neural Diffusion Processes. NeurIPS (2023)
Louis C. Tiao, Vincent Dutordoir, Victor Picheny
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes. ICML (2023)
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
Memory-Based Meta-Learning on Non-Stationary Distributions. ICML (2023)
Louis C. Tiao, Vincent Dutordoir, Victor Picheny
Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes. CoRR (2023)
Vincent Dutordoir, Alan Saul, Zoubin Ghahramani, Fergus Simpson
Neural Diffusion Processes. ICML (2023)
Vincent Dutordoir, Alan Saul, Zoubin Ghahramani, Fergus Simpson
Neural Diffusion Processes. CoRR (2022)
Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande
Deep Neural Networks as Point Estimates for Deep Gaussian Processes. CoRR (2021)
Sattar Vakili, Henry B. Moss, Artem Artemev, Vincent Dutordoir, Victor Picheny
Scalable Thompson Sampling using Sparse Gaussian Process Models. NeurIPS (2021)
Vincent Dutordoir, Hugh Salimbeni, Eric Hambro, John McLeod, Felix Leibfried, Artem Artemev, Mark van der Wilk, James Hensman, Marc Peter Deisenroth, S. T. John
GPflux: A Library for Deep Gaussian Processes. CoRR (2021)
Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande
Deep Neural Networks as Point Estimates for Deep Gaussian Processes. NeurIPS (2021)
Nicolas Knudde, Vincent Dutordoir, Joachim van der Herten, Ivo Couckuyt, Tom Dhaene
Hierarchical Gaussian Process Models for Improved Metamodeling. ACM Trans. Model. Comput. Simul. 30 (4) (2020)
Vincent Dutordoir, Mark van der Wilk, Artem Artemev, James Hensman
Bayesian Image Classification with Deep Convolutional Gaussian Processes. AISTATS (2020)
Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. CoRR (2020)
Felix Leibfried, Vincent Dutordoir, S. T. John, Nicolas Durrande
A Tutorial on Sparse Gaussian Processes and Variational Inference. CoRR (2020)
Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande
Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. ECML/PKDD (3) (2020)
Mark van der Wilk, Vincent Dutordoir, S. T. John, Artem Artemev, Vincent Adam, James Hensman
A Framework for Interdomain and Multioutput Gaussian Processes. CoRR (2020)
Vincent Dutordoir, Nicolas Durrande, James Hensman
Sparse Gaussian Processes with Spherical Harmonic Features. CoRR (2020)
Vincent Dutordoir, Nicolas Durrande, James Hensman
Sparse Gaussian Processes with Spherical Harmonic Features. ICML (2020)
Hugh Salimbeni, Vincent Dutordoir, James Hensman, Marc Peter Deisenroth
Deep Gaussian Processes with Importance-Weighted Variational Inference. ICML (2019)
Vincent Dutordoir, Mark van der Wilk, Artem Artemev, Marcin Tomczak, James Hensman
Translation Insensitivity for Deep Convolutional Gaussian Processes. CoRR (2019)
Hugh Salimbeni, Vincent Dutordoir, James Hensman, Marc Peter Deisenroth
Deep Gaussian Processes with Importance-Weighted Variational Inference. CoRR (2019)
Vincent Dutordoir, Hugh Salimbeni, James Hensman, Marc Peter Deisenroth
Gaussian Process Conditional Density Estimation. NeurIPS (2018)
Vincent Dutordoir, Hugh Salimbeni, Marc Peter Deisenroth, James Hensman
Gaussian Process Conditional Density Estimation. CoRR (2018)
Vincent Dutordoir, Nicolas Knudde, Joachim van der Herten, Ivo Couckuyt, Tom Dhaene
Deep Gaussian Process metamodeling of sequentially sampled non-stationary response surfaces. WSC (2017)