Sara Wade

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10 Article
1 Conference contribution
1 Paper
1 Review article

Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences
Leist, A. K., Klee, M., Kim, J. H., Rehkopf, D. H., Bordas, S. P. A., Muniz-Terrera, G. & Wade, S., 19 Oct 2022, In: Science Advances. 8, 42, p. eabk1942
Research output: Contribution to journal › Review article › peer-review

Open Access
File
Machine Learning in Health and Social Science
Leist, A. K., Klee, M., Jung, H. K., Rehkopf, D. H., Terrera, G. M. & Wade, S. K., 31 Aug 2022, (Accepted/In press).
Research output: Contribution to conference › Paper › peer-review

File
Bayesian nonparametric scalar-on-image regression via Potts-Gibbs random partition models
Wade, S. K. & Xian, M. T. S., 23 Jun 2022, (Accepted/In press) BAyesian Young Statisticians Meeting 2021. Springer, (Springer Proceedings in Mathematics & Statistics).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
File
Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data
Yu, W., Wade, S. K., Bondell, H. D. & Azizi, L., 23 Jun 2022, (Accepted/In press) In: Journal of Computational and Graphical Statistics.
Research output: Contribution to journal › Article › peer-review

Open Access
File
Pseudo-marginal Bayesian inference for Gaussian process latent variable models
Gadd, C., Wade, S. K. & Shah, A. A., 30 Jun 2021, In: Machine Learning. 110, p. 1105–1143 39 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File

2 Finished

Bayesian Statistical Learning for Integrative Imaging in Alzheimer's Diagnosis
Wade, S.
UK-based charities
1/06/21 → 31/07/22
Project: Research
Wade Prowler Collaboration
Wade, S.
UK industry, commerce and public corporations
19/08/19 → 18/01/20
Project: Research

Sara Wade

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Dive into details

Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences

Machine Learning in Health and Social Science

Bayesian nonparametric scalar-on-image regression via Potts-Gibbs random partition models

Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data

Pseudo-marginal Bayesian inference for Gaussian process latent variable models

Bayesian Statistical Learning for Integrative Imaging in Alzheimer's Diagnosis

Wade Prowler Collaboration

Sara Wade

Fingerprint

Network

Research output

Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences

Machine Learning in Health and Social Science

Bayesian nonparametric scalar-on-image regression via Potts-Gibbs random partition models

Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data

Pseudo-marginal Bayesian inference for Gaussian process latent variable models

Projects

Bayesian Statistical Learning for Integrative Imaging in Alzheimer's Diagnosis

Wade Prowler Collaboration