1 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Leveraging variational autoencoders for multiple data imputation
Breeshey Roskams-Hieter, Jude Wells, Sara Wade
Missing data persists as a major barrier to data analysis across numerous applications. Recently, deep generative models have been used for imputation of missing data, motivated by…
Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data
W Yu, S Wade, H D Bondell +1
High-dimensional classification and feature selection tasks are ubiquitous with the recent advancement in data acquisition technology. In several application areas such as biology,…
Enriched Mixtures of Gaussian Process Experts
Charles W. L. Gadd, Sara Wade, Alexis Boukouvalas
Mixtures of experts probabilistically divide the input space into regions, where the assumptions of each expert, or conditional model, need only hold locally. Combined with Gaussia…
Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models
Charles Gadd, Sara Wade, Akeel Shah +1
We introduce a Bayesian framework for inference with a supervised version of the Gaussian process latent variable model. The framework overcomes the high correlations between laten…