Sparse convolved gaussian processes for multi-output regression, Advances in Neural Information Processing Systems 21, pp.57-64, 2009. ,
Latent force models, AISTATS, volume 5 of JMLR Proceedings, pp.9-16, 2009. ,
URL : https://hal.archives-ouvertes.fr/hal-01864351
Efficient multioutput gaussian processes through variational inducing kernels, AISTATS, volume 9 of JMLR Proceedings, pp.25-32, 2010. ,
Multitask gaussian process prediction, Advances in Neural Information Processing Systems, pp.153-160, 2008. ,
Dependent gaussian processes, Advances in Neural Information Processing Systems 17, pp.217-224, 2005. ,
Physicsbased covariance models for gaussian processes with multiple outputs, International Journal for Uncertainty Quantification, vol.3, 2013. ,
Distributed gaussian processes, Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, pp.6-11, 2015. ,
A unifying view of sparse approximate gaussian process regression, Journal of Machine Learning Research, vol.6, 2005. ,
Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning), 2005. ,
Sparse gaussian processes using pseudo-inputs, In ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS, pp.1257-1264, 2006. ,
Derivative observations in gaussian process models of dynamic systems, Advances in Neural Information Processing Systems 15, pp.1057-1064, 2003. ,
Interpolation of Spatial Data: Some Theory for Kriging, 1999. ,
DOI : 10.1007/978-1-4612-1494-6
Variational learning of inducing variables in sparse gaussian processes, In In Artificial Intelligence and Statistics, vol.12, pp.567-574, 2009. ,
Gpstuff: Bayesian modeling with gaussian processes, J. Mach. Learn. Res, vol.14, issue.1, pp.1175-1179, 2013. ,