:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lindley, C. A., Dervilis, N., Worden, K.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2501.08050
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multi-Task Equation Discovery
by: Bee, S C, et al.
Published: (2025)

Anomaly Detection in Offshore Wind Turbine Structures using Hierarchical Bayesian Modelling
by: Smith, S. M., et al.
Published: (2024)

On the hierarchical Bayesian modelling of frequency response functions
by: Dardeno, T. A., et al.
Published: (2023)

Towards a population-informed approach to the definition of data-driven models for structural dynamics
by: Tsialiamanis, G., et al.
Published: (2023)

Regularising NARX models with multi-task learning
by: Bee, Sarah, et al.
Published: (2025)

Physics-informed transfer learning for SHM via feature selection
by: Poole, J., et al.
Published: (2025)

When does a bridge become an aeroplane?
by: Dardeno, Tina A., et al.
Published: (2024)

Inter-turbine Modelling of Wind-Farm Power using Multi-task Learning
by: Brealy, Simon M., et al.
Published: (2025)

Towards an active-learning approach to resource allocation for population-based damage prognosis
by: Tsialiamanis, George, et al.
Published: (2024)

Transfer learning via interpolating structures
by: Dardeno, T. A., et al.
Published: (2026)

Cost-informed dimensionality reduction for structural digital twin technologies
by: Hughes, Aidan J., et al.
Published: (2024)

Active transfer learning for structural health monitoring
by: Poole, J., et al.
Published: (2025)

Quantifying the value of positive transfer: An experimental case study
by: Hughes, Aidan J., et al.
Published: (2024)

Canonical-Correlation-Based Fast Feature Selection for Structural Health Monitoring
by: Zhang, Sikai, et al.
Published: (2021)

On Additive Gaussian Processes for Wind Farm Power Prediction
by: Brealy, Simon M., et al.
Published: (2026)

Multitask learning for improved scour detection: A dynamic wave tank study
by: Brealy, Simon M., et al.
Published: (2024)

Active learning for regression in engineering populations: A risk-informed approach
by: Clarkson, Daniel R., et al.
Published: (2024)

Green Physics-Informed Machine Learning Models For Structural Health Monitoring
by: Bradley, Daisy R, et al.
Published: (2026)

A Machine Learning-Driven Wireless System for Structural Health Monitoring
by: Pop, Marius, et al.
Published: (2024)

On-Device Crack Segmentation for Edge Structural Health Monitoring
by: Zhang, Yuxuan, et al.
Published: (2025)

Statistically Valid Post-Deployment Monitoring Should Be Standard for AI-Based Digital Health
by: Dolin, Pavel, et al.
Published: (2025)

Conditional deep generative models as surrogates for spatial field solution reconstruction with quantified uncertainty in Structural Health Monitoring applications
by: Silionis, Nicholas E., et al.
Published: (2023)

Statistical Learning Theory for Distributional Classification
by: Fiedler, Christian
Published: (2026)

Machine Learning Algorithms in Statistical Modelling Bridging Theory and Application
by: Rao, A. Ganapathi, et al.
Published: (2025)

A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
by: Lin, Licong, et al.
Published: (2025)

Engineering Microbial Symbiosis for Mars Habitability
by: Correll, Randall R., et al.
Published: (2025)

Hybrid Spectro-Temporal Fusion Framework for Structural Health Monitoring
by: Kim, Jongyeop, et al.
Published: (2026)

Cardiac Stability Theory: An Axiomatically Grounded Framework for Continuous Cardiac Health Monitoring via Smartphone Photoplethysmography
by: Oladunni, Timothy, et al.
Published: (2026)

Active Learning for WBAN-based Health Monitoring
by: Chiu, Cho-Chun, et al.
Published: (2024)

Extrapolation in Statistical Learning with Extreme Value Theory
by: Engelke, Sebastian, et al.
Published: (2026)

Statistical inference after variable selection in Cox models: A simulation study
by: Schemet, Lena, et al.
Published: (2026)

Time-Vertex Machine Learning for Optimal Sensor Placement in Temporal Graph Signals: Applications in Structural Health Monitoring
by: Niresi, Keivan Faghih, et al.
Published: (2025)

What is in the model? A Comparison of variable selection criteria and model search approaches
by: Xu, Shuangshuang, et al.
Published: (2025)

Group selection and shrinkage: Structured sparsity for semiparametric additive models
by: Thompson, Ryan, et al.
Published: (2021)

Foundation Models for Structural Health Monitoring
by: Benfenati, Luca, et al.
Published: (2024)

A Statistical Theory of Regularization-Based Continual Learning
by: Zhao, Xuyang, et al.
Published: (2024)

Towards a Universal Vibration Analysis Dataset: A Framework for Transfer Learning in Predictive Maintenance and Structural Health Monitoring
by: Sehri, Mert, et al.
Published: (2025)

Information Theory and Statistical Learning
by: Gamal, Abbas El
Published: (2026)

Statistical Properties of the log-cosh Loss Function Used in Machine Learning
by: Saleh, Resve A., et al.
Published: (2022)

On the topology and geometry of population-based SHM
by: Worden, Keith, et al.
Published: (2024)