research
∙
03/14/2022
Modelling Non-Smooth Signals with Complex Spectral Structure
The Gaussian Process Convolution Model (GPCM; Tobar et al., 2015a) is a ...
share
research
∙
12/07/2021
A Bayesian take on option pricing with Gaussian processes
Local volatility is a versatile option pricing model due to its state de...
research
∙
06/21/2021
Data Optimisation for a Deep Learning Recommender System
This paper advocates privacy preserving requirements on collection of us...
research
∙
03/22/2019
A Machine Learning approach to Risk Minimisation in Electricity Markets with Coregionalized Sparse Gaussian Processes
The non-storability of electricity makes it unique among commodity asset...
research
∙
07/13/2018
Sequential sampling of Gaussian process latent variable models
We consider the problem of inferring a latent function in a probabilisti...
research
∙
07/13/2018
