5 citations · 10 across the 5 of their papers we have counts for
5 papers
Characterising harmful data sources when constructing multi-fidelity surrogate models
Nicolau Andrés-Thió, Mario Andrés Muñoz, Kate Smith-Miles
Surrogate modelling techniques have seen growing attention in recent years when applied to both modelling and optimisation of industrial design problems. These techniques are highl…
On the Instance Dependence of Optimal Parameters for the Quantum Approximate Optimisation Algorithm: Insights via Instance Space Analysis
Vivek Katial, Kate Smith-Miles, Charles Hill
The performance of the Quantum Approximate Optimisation Algorithm (QAOA) relies on the setting of optimal parameters in each layer of the circuit. This is no trivial task, and much…
Comprehensive Algorithm Portfolio Evaluation using Item Response Theory
Sevvandi Kandanaarachchi, Kate Smith-Miles
Item Response Theory (IRT) has been proposed within the field of Educational Psychometrics to assess student ability as well as test question difficulty and discrimination power. M…
An Efficient Transformer for Simultaneous Learning of BEV and Lane Representations in 3D Lane Detection
Ziye Chen, Kate Smith-Miles, Bo Du +2
Accurately detecting lane lines in 3D space is crucial for autonomous driving. Existing methods usually first transform image-view features into bird-eye-view (BEV) by aid of inver…
Can Deep Learning Assist Automatic Identification of Layered Pigments From XRF Data?
Bingjie, Xu, Yunan Wu +12
X-ray fluorescence spectroscopy (XRF) plays an important role for elemental analysis in a wide range of scientific fields, especially in cultural heritage. XRF imaging, which uses…