activity
20222026
most citedActive learning for regression in engineering populations: A risk-informed approach

1 citations · 2 across the 10 of their papers we have counts for

collaborators
Showing cs.LGShow all

9 papers · 1 filter

cs.LG2026

Transfer learning via interpolating structures

T. A. Dardeno, A. J. Hughes, L. A. Bull +3

Despite recent advances in population-based structural health monitoring (PBSHM), knowledge transfer between highly-disparate structures (i.e., heterogeneous populations) remains a…

cs.LG2025

Physics-informed transfer learning for SHM via feature selection

J. Poole, P. Gardner, A. J. Hughes +4

Data used for training structural health monitoring (SHM) systems are expensive and often impractical to obtain, particularly labelled data. Population-based SHM presents a potenti…

cs.LG2024

When does a bridge become an aeroplane?

Tina A. Dardeno, Lawrence A. Bull, Nikolaos Dervilis +1

Despite recent advances in population-based structural health monitoring (PBSHM), knowledge transfer between highly-disparate structures (i.e., heterogeneous populations) remains a…

cs.LG2024★ 1 cited

Active learning for regression in engineering populations: A risk-informed approach

Daniel R. Clarkson, Lawrence A. Bull, Chandula T. Wickramarachchi +5

Regression is a fundamental prediction task common in data-centric engineering applications that involves learning mappings between continuous variables. In many engineering applic…

cs.LG2024

Multitask learning for improved scour detection: A dynamic wave tank study

Simon M. Brealy, Aidan J. Hughes, Tina A. Dardeno +4

Population-based structural health monitoring (PBSHM), aims to share information between members of a population. An offshore wind (OW) farm could be considered as a population of…

cs.LG2024

Anomaly Detection in Offshore Wind Turbine Structures using Hierarchical Bayesian Modelling

S. M. Smith, A. J. Hughes, T. A. Dardeno +3

Population-based structural health monitoring (PBSHM), aims to share information between members of a population. An offshore wind (OW) farm could be considered as a population of…

cs.LG2023

Sharing Information Between Machine Tools to Improve Surface Finish Forecasting

Daniel R. Clarkson, Lawrence A. Bull, Tina A. Dardeno +6

At present, most surface-quality prediction methods can only perform single-task prediction which results in under-utilised datasets, repetitive work and increased experimental cos…

cs.LG2022

A generalised form for a homogeneous population of structures using an overlapping mixture of Gaussian processes

Tina A. Dardeno, Lawrence A. Bull, Nikolaos Dervilis +1

Reductions in natural frequency are often used as a damage indicator for structural health monitoring (SHM) purposes. However, fluctuations in operational and environmental conditi…

cs.LG2022★ 1 cited

Modelling variability in vibration-based PBSHM via a generalised population form

Tina A Dardeno, Lawrence A Bull, Robin S Mills +2

Structural health monitoring (SHM) has been an active research area for the last three decades, and has accumulated a number of critical advances over that period, as can be seen i…