Nicolas Durrande

According to our database, Nicolas Durrande authored at least 23 papers between 2013 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

Bayesian quantile and expectile optimisation.

Victor Picheny, Henry B. Moss, Léeonard Torossian, Nicolas Durrande

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Physically-Inspired Gaussian Process Models for Post-Transcriptional Regulation in Drosophila.

Andrés F. López-Lopera, Nicolas Durrande, Mauricio A. Álvarez

IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Kernel Identification Through Transformers.

Fergus Simpson, Ian Davies, Vidhi Lalchand, Alessandro Vullo, Nicolas Durrande, Carl Edward Rasmussen

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Neural Networks as Point Estimates for Deep Gaussian Processes.

Vincent Dutordoir, James Hensman, Mark van der Wilk, Carl Henrik Ek, Zoubin Ghahramani, Nicolas Durrande

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain.

Fergus Simpson, Alexis Boukouvalas, Václav Cadek, Elvijs Sarkans, Nicolas Durrande

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Matérn Gaussian Processes on Graphs.

Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

A Tutorial on Sparse Gaussian Processes and Variational Inference.

Felix Leibfried, Vincent Dutordoir, S. T. John, Nicolas Durrande

CoRR, 2020

Regret Bounds for Noise-Free Bayesian Optimization.

Sattar Vakili, Victor Picheny, Nicolas Durrande

CoRR, 2020

Bayesian Quantile and Expectile Optimisation.

Léonard Torossian, Victor Picheny, Nicolas Durrande

CoRR, 2020

Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation.

Victor Picheny, Vincent Dutordoir, Artem Artemev, Nicolas Durrande

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Sparse Gaussian Processes with Spherical Harmonic Features.

Vincent Dutordoir, Nicolas Durrande, James Hensman

Proceedings of the 37th International Conference on Machine Learning, 2020

Doubly Sparse Variational Gaussian Processes.

Vincent Adam, Stefanos Eleftheriadis, Artem Artemev, Nicolas Durrande, James Hensman

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Approximating Gaussian Process Emulators with Linear Inequality Constraints and Noisy Observations via MC and MCMC.

Andrés F. López-Lopera, François Bachoc, Nicolas Durrande, Olivier Roustant

CoRR, 2019

Gaussian Process Modulated Cox Processes under Linear Inequality Constraints.

Andrés F. López-Lopera, S. T. John, Nicolas Durrande

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era.

Nicolas Durrande, Vincent Adam, Lucas Bordeaux, Stefanos Eleftheriadis, James Hensman

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Nested Kriging predictions for datasets with a large number of observations.

Didier Rullière, Nicolas Durrande, François Bachoc, Clément Chevalier

Stat. Comput., 2018

Finite-Dimensional Gaussian Approximation with Linear Inequality Constraints.

Andrés F. López-Lopera, François Bachoc, Nicolas Durrande, Olivier Roustant

SIAM/ASA J. Uncertain. Quantification, 2018

Scalable GAM using sparse variational Gaussian processes.

Vincent Adam, Nicolas Durrande, S. T. John

CoRR, 2018

Physically-inspired Gaussian processes for transcriptional regulation in Drosophila melanogaster.

Andrés F. López-Lopera, Nicolas Durrande, Mauricio A. Álvarez

CoRR, 2018

2017

Variational Fourier Features for Gaussian Processes.

James Hensman, Nicolas Durrande, Arno Solin

J. Mach. Learn. Res., 2017

2016

Detecting periodicities with Gaussian processes.

Nicolas Durrande, James Hensman, Magnus Rattray, Neil D. Lawrence

PeerJ Prepr., 2016

2014

On ANOVA Decompositions of Kernels and Gaussian Random Field Paths.

David Ginsbourger, Olivier Roustant, Dominic Schuhmacher, Nicolas Durrande, Nicolas Lenz

Proceedings of the Monte Carlo and Quasi-Monte Carlo Methods, 2014

2013

ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis.

Nicolas Durrande, David Ginsbourger, Olivier Roustant, Laurent Carraro

J. Multivar. Anal., 2013