Nicolas Durrande

1. Variational Fourier features for Gaussian processes
   2016/11/21 by James Hensman, Nicolas Durrande, Hensman, James +3 · 28 citations
   Computer Science · Physics and Astronomy · #Gaussian Processes and Bayesian Inference #Scientific Research and Discoveries #Advanced Multi-Objective Optimization Algorithms
2. A Tutorial on Sparse Gaussian Processes and Variational Inference
   2020/12/27 by Felix Leibfried, Leibfried, Felix, Vincent Dutordoir +5 · 6 citations
   Computer Science · Engineering · #Gaussian Processes and Bayesian Inference #Machine Learning and Algorithms #Control Systems and Identification
3. Additive Kernels for Gaussian Process Modeling
   2011/03/21 by Nicolas Durrande, David Ginsbourger, Durrande, Nicolas +3 · 2 citations
   Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Probabilistic and Robust Engineering Design
4. Invariances of random fields paths, with applications in Gaussian Process Regression
   2013/08/06 by David Ginsbourger, Olivier Roustant, Ginsbourger, David +3 · 2 citations
   Computer Science · Decision Sciences · #Gaussian Processes and Bayesian Inference #Advanced Multi-Objective Optimization Algorithms #Probabilistic and Robust Engineering Design
5. Kernel Identification Through Transformers
   2021/06/15 by Fergus Simpson, Simpson, Fergus, Ian Davies +9 · 2 citations
   Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
6. Gaussian process models for periodicity detection
   2013/03/28 by Nicolas Durrande, Durrande, Nicolas, James Hensman +5 · 1 citation
   Computer Science · #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Statistics Theory (math.ST) #Target Tracking and Data Fusion in Sensor Networks
7. On ANOVA decompositions of kernels and Gaussian random field paths
   2014/09/21 by David Ginsbourger, Ginsbourger, David, Olivier Roustant +7 · 1 citation
   Computer Science · Decision Sciences · Physics and Astronomy · #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Model Reduction and Neural Networks #Probabilistic and Robust Engineering Design #Probability (math.PR) #Statistics Theory (math.ST)
8. Nested Kriging predictions for datasets with large number of observations
   2016/07/19 by Didier Rullière, Rullière, Didier, Nicolas Durrande +5 · 1 citation
   Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Optimal Experimental Design Methods
9. Nested Kriging predictions for datasets with a large number of observations
   2017/07/26 by Didier Rullière, Nicolas Durrande, François Bachoc +1 · 3 citations
   Computer Science · Decision Sciences · #Advanced Multi-Objective Optimization Algorithms #Optimal Experimental Design Methods #Gaussian Processes and Bayesian Inference