All Outputs (35)

Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics (2023)
Journal Article

When using mathematical models to make quantitative predictions for clinical or industrial use, it is important that predictions come with a reliable estimate of their accuracy (uncertainty quantification). Because models of complex biological system... Read More about Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics.

Uncertainty and error in SARS-CoV-2 epidemiological parameters inferred from population-level epidemic models (2022)
Journal Article

During the SARS-CoV2 pandemic, epidemic models have been central to policy-making. Public health responses have been shaped by model-based projections and inferences, especially related to the impact of various non-pharmaceutical interventions. Accom... Read More about Uncertainty and error in SARS-CoV-2 epidemiological parameters inferred from population-level epidemic models.

Modelling reveals post-transcriptional regulation of GA metabolism enzymes in response to drought and cold (2022)
Journal Article

The hormone gibberellin (GA) controls plant growth and regulates growth responses to environmental stress. In monocotyledonous leaves, GA controls growth by regulating division-zone size. We used a systems approach to investigate the establishment of... Read More about Modelling reveals post-transcriptional regulation of GA metabolism enzymes in response to drought and cold.

Manifold valued data analysis of samples of networks, with applications in corpus linguistics (2022)
Journal Article

Networks arise in many applications, such as in the analysis of text documents, social interactions and brain activity. We develop a general framework for extrinsic statistical analysis of samples of networks, motivated by networks representing text... Read More about Manifold valued data analysis of samples of networks, with applications in corpus linguistics.

The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania (2022)
Journal Article

Identifying the most deprived regions of any country or city is key if policy makers are to design successful interventions. However, locating areas with the greatest need is often surprisingly challenging in developing countries. Due to the logistic... Read More about The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania.

Gaussian process models of potential energy surfaces with boundary optimization (2021)
Journal Article

A strategy is outlined to reduce the number of training points required to model intermolecular potentials using Gaussian processes, without reducing accuracy. An asymptotic function is used at a long range, and the crossover distance between this mo... Read More about Gaussian process models of potential energy surfaces with boundary optimization.

Gaussian Process Models of Potential Energy Surfaces with Boundary Optimisation (2021)
Journal Article

A strategy is outlined to reduce the number of training points required to model intermolecular potentials using Gaussian processes, without reducing accuracy. An asymptotic function is used at long range and the cross-over distance between this mode... Read More about Gaussian Process Models of Potential Energy Surfaces with Boundary Optimisation.

Approximate Maximum Likelihood Estimation for One-Dimensional Diffusions Observed on a Fine Grid (2021)
Journal Article

We consider a one-dimensional stochastic differential equation that is observed on a fine grid of equally spaced time points. A novel approach for approximating the transition density of the stochastic differential equation is presented, which is bas... Read More about Approximate Maximum Likelihood Estimation for One-Dimensional Diffusions Observed on a Fine Grid.

Non?parametric regression for networks (2021)
Journal Article

Network data are becoming increasingly available, and so there is a need to develop suitable methodology for statistical analysis. Networks can be represented as graph Laplacian matrices, which are a type of manifold-valued data. Our main objective i... Read More about Non?parametric regression for networks.

Positioning the Root Elongation Zone Is Saltatory and Receives Input from the Shoot (2020)
Journal Article

In the root, meristem and elongation zone lengths remain stable, despite growth and division of cells. To gain insight into zone stability, we imaged individual Arabidopsis thaliana roots through a horizontal microscope, and used image analysis to ob... Read More about Positioning the Root Elongation Zone Is Saltatory and Receives Input from the Shoot.

Invariance and identifiability issues for word embeddings (2019)
Conference Proceeding

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

Lacunarity of the zero crossings of Gaussian processes (2019)
Journal Article

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

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

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.

Parameter inference to motivate asymptotic model reduction: an analysis of the gibberellin biosynthesis pathway (2018)
Journal Article

Developing effective strategies to use models in conjunction with experimental data is essential to understand the dynamics of biological regulatory networks. In this study, we demonstrate how combining parameter estimation with asymptotic analysis c... Read More about Parameter inference to motivate asymptotic model reduction: an analysis of the gibberellin biosynthesis pathway.

Process parameter optimisation of laser clad iron based alloy: Predictive models of deposition efficiency, porosity and dilution (2018)
Journal Article

As a candidate coating material for heat-exchanger surfaces in commercial power generation boiler, an amorphous/glass forming Fe-Cr-B alloy NanoSteel SHS 7170 was deposited by a 2 kW fibre laser onto a boiler grade steel substrate (15Mo3). A comprehe... Read More about Process parameter optimisation of laser clad iron based alloy: Predictive models of deposition efficiency, porosity and dilution.

Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies (2018)
Journal Article

Background and Aims Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the comp... Read More about Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies.

Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies (2018)
Working Paper

Background and Aims Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the comp... Read More about Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies.

An elliptically symmetric angular Gaussian distribution (2017)
Journal Article

We define a distribution on the unit sphere Sd−1 called the elliptically symmetric angular Gaussian distribution. This distribution, which to our knowledge has not been studied before, is a subfamily of the angular Gaussian distribution closely analo... Read More about An elliptically symmetric angular Gaussian distribution.