5 papers
Fast simulation of Volterra processes using random Fourier features with application to the log-stationary fractional Brownian motion
Othmane Zarhali, Nicolas Langrené
A fast simulation framework for stochastic Volterra processes based on Random Fourier Features (RFF) approximation of the kernel is developed. After recalling the main properties o…
Scalable method for mean field control with kernel interactions via random Fourier features
Zhongyuan Cao, Kaustav Das, Nicolas Langrené +1
We develop a scalable algorithm for mean field control problems with kernel interactions by combining particle system simulations with random Fourier feature approximations. The me…
The dynamics of innovation diffusion: A survey of Bass-type models
Nicolas Langrené, Rui Liu, Xiangqin Wu +1
This paper synthesises the existing research on the dynamics of innovation diffusion, with a focus on Bass-type models and their extensions. The theoretical foundation of innovatio…
A spectral mixture representation of isotropic kernels with application to random Fourier features
Nicolas Langrené, Xavier Warin, Pierre Gruet
Rahimi and Recht (2007) introduced the idea of decomposing positive definite shift-invariant kernels by randomly sampling from their spectral distribution for machine learning appl…
Fast Gaussian process inference by exact Matérn kernel decomposition
Nicolas Langrené, Xavier Warin, Pierre Gruet
To speed up Gaussian process inference, a number of fast kernel matrix-vector multiplication (MVM) approximation algorithms have been proposed over the years. In this paper, we est…