Sara Wade

Reader in Statistics and Data Science


Curriculum vitae


[email protected]


School of Mathematics

University of Edinburgh

Room 5406
James Clerk Maxwell Building, Edinburgh, EH9 3FD



Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models


Journal article


C. Gadd, S. Wade, A. Shah
Machine Learning, vol. 110, 2021, pp. 1105-1143


Paper
Cite

Cite

APA   Click to copy
Gadd, C., Wade, S., & Shah, A. (2021). Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models. Machine Learning, 110, 1105–1143. https://doi.org/10.1007/s10994-021-05971-2


Chicago/Turabian   Click to copy
Gadd, C., S. Wade, and A. Shah. “Pseudo-Marginal Bayesian Inference for Supervised Gaussian Process Latent Variable Models.” Machine Learning 110 (2021): 1105–1143.


MLA   Click to copy
Gadd, C., et al. “Pseudo-Marginal Bayesian Inference for Supervised Gaussian Process Latent Variable Models.” Machine Learning, vol. 110, 2021, pp. 1105–43, doi:10.1007/s10994-021-05971-2.


BibTeX   Click to copy

@article{gadd2021a,
  title = {Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models},
  year = {2021},
  journal = {Machine Learning},
  pages = {1105-1143},
  volume = {110},
  doi = {10.1007/s10994-021-05971-2},
  author = {Gadd, C. and Wade, S. and Shah, A.}
}


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