Professor SIMON PRESTON's Outputs (5)

Invariance and identifiability issues for word embeddings (2019)
Presentation / Conference Contribution
Carrington, R., Bharath, K., & Preston, S. (2019, December). Invariance and identifiability issues for word embeddings. Presented at NeurIPS 2019, Vancouver, Canada

Word embeddings are commonly obtained as optimisers of a criterion function f of 1 a text corpus, but assessed on word-task performance using a different evaluation 2 function g of the test data. We contend that a possible source of disparity in 3 pe... Read More about Invariance and identifiability issues for word embeddings.

Discussion: Object-Oriented Data Analysis, Power Metrics, and Graph Laplacians (2019)
Journal Article
Severn, K. E., Dryden, I. L., Preston, S. P., & Severn, K. E. (2019). Discussion: Object-Oriented Data Analysis, Power Metrics, and Graph Laplacians. Journal of the American Statistical Association, 114(527), 1097-1098. https://doi.org/10.1080/01621459.2019.1635477

Lacunarity of the zero crossings of Gaussian processes (2019)
Journal Article
Ogunshemi, A., Hopcraft, K. I., & Preston, S. P. (2019). Lacunarity of the zero crossings of Gaussian processes. Physical Review E, 99(6), Article 062109. https://doi.org/10.1103/physreve.99.062109

A lacunarity analysis of the zero-crossings derived from Gaussian stochastic processes with oscillatory autocorrelation functions is evaluated and reveals distinct multi-scaling signatures depending on the smoothness and degree of anti-correlation of... Read More about Lacunarity of the zero crossings of Gaussian processes.

Spherical regression models with general covariates and anisotropic errors (2019)
Journal Article
Paine, P. J., Preston, S. P., Tsagris, M., & Wood, A. T. A. (2020). Spherical regression models with general covariates and anisotropic errors. Statistics and Computing, 30(1), 153–165. https://doi.org/10.1007/s11222-019-09872-2

Existing parametric regression models in the literature for response data on the unit sphere assume that the covariates have particularly simple structure, for example that they are either scalar or are themselves on the unit sphere, and/or that the... Read More about Spherical regression models with general covariates and anisotropic errors.

Quantifying age and model uncertainties in palaeoclimate data and dynamical climate models with a joint inferential analysis (2019)
Journal Article
Carson, J., Crucifix, M., Preston, S., & Wilkinson, R. (2019). Quantifying age and model uncertainties in palaeoclimate data and dynamical climate models with a joint inferential analysis. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 475(2224), https://doi.org/10.1098/rspa.2018.0854

The study of palaeoclimates relies on information sampled in natural archives such as deep sea cores. Scientific investigations often use such information in multi- stage analyses, typically with an age model being fitted to a core to convert depths... Read More about Quantifying age and model uncertainties in palaeoclimate data and dynamical climate models with a joint inferential analysis.