Emulation of random output simulators. - Alexis Boukouvalas (2010)

Gaussian Process Quantile Regression using Expectation Propagation. - Alexis Boukouvalas; Remi Louis Barillec; Dan Cornford (ICML, 2012)

Optimal design for correlated processes with input-dependent noise. - Alexis Boukouvalas; Dan Cornford; Milan Stehlík (Comput. Stat. Data Anal., 2014)

An Efficient Screening Method for Computer Experiments. - Alexis Boukouvalas; John Paul Gosling; Hugo Maruri-Aguilar (Technometrics, 2014)

Bayesian Precalibration of a Large Stochastic Microsimulation Model. - Alexis Boukouvalas; Pete Sykes; Dan Cornford; Hugo Maruri-Aguilar (IEEE Trans. Intell. Transp. Syst., 2014)

Predicting room occupancy with a single passive infrared (PIR) sensor through behavior extraction. - Yordan P. Raykov; Emre Ozer 001; Ganesh Dasika; Alexis Boukouvalas; Max A. Little (UbiComp, 2016)

GPflow: A Gaussian Process Library using TensorFlow. - Alexander G. de G. Matthews; Mark van der Wilk; Tom Nickson; Keisuke Fujii 002; Alexis Boukouvalas; Pablo León-Villagrá; Zoubin Ghahramani; James Hensman (J. Mach. Learn. Res., 2017)

Decision Variance in Online Learning. - Sattar Vakili; Alexis Boukouvalas (CoRR, 2018)

Decision Variance in Risk-Averse Online Learning. - Sattar Vakili; Alexis Boukouvalas; Qing Zhao 001 (CDC, 2019)

Adaptive Sensor Placement for Continuous Spaces. - James A. Grant; Alexis Boukouvalas; Ryan-Rhys Griffiths; David S. Leslie; Sattar Vakili; Enrique Munoz de Cote (ICML, 2019)

GrandPrix: scaling up the Bayesian GPLVM for single-cell data. - Sumon Ahmed; Magnus Rattray; Alexis Boukouvalas (Bioinform., 2019)

Enriched Mixtures of Gaussian Process Experts. - Charles W. L. Gadd; Sara Wade; Alexis Boukouvalas (CoRR, 2019)

Enriched mixtures of generalised Gaussian process experts. - Charles W. L. Gadd; Sara Wade; Alexis Boukouvalas (AISTATS, 2020)

OscoNet: inferring oscillatory gene networks. - Luisa Cutillo; Alexis Boukouvalas; Elli Marinopoulou; Nancy Papalopulu; Magnus Rattray (BMC Bioinform., 2020)

The Minecraft Kernel: Modelling correlated Gaussian Processes in the Fourier domain. - Fergus Simpson; Alexis Boukouvalas; Václav Cadek; Elvijs Sarkans; Nicolas Durrande (AISTATS, 2021)

Non-parametric modelling of temporal and spatial counts data from RNA-seq experiments. - Nuha Bintayyash; Sokratia Georgaka; S. T. John; Sumon Ahmed; Alexis Boukouvalas; James Hensman; Magnus Rattray (Bioinform., 2021)

Additive Gaussian Processes Revisited. - Xiaoyu Lu; Alexis Boukouvalas; James Hensman (ICML, 2022)

Modelling sequential branching dynamics with a multivariate branching Gaussian process. - Elvijs Sarkans; Sumon Ahmed; Magnus Rattray; Alexis Boukouvalas (Trans. Mach. Learn. Res., 2023)

AlphaEarth Foundations: An embedding field model for accurate and efficient global mapping from sparse label data. - Christopher F. Brown; Michal Kazmierski; Valerie Pasquarella; William Rucklidge; Masha Samsikova; Chenhui Zhang; Evan Shelhamer; Estefania Lahera; Olivia Wiles; Simon Ilyushchenko; Noel Gorelick; Lihui Lydia Zhang; et al. (CoRR, 2025)