Foundations of population-based SHM, Part III: Heterogeneous populations – Mapping and transfer von Gardner, P., Bull, L.A., Gosliga, J., Dervilis, N., Worden, K.

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Active learning for semi-supervised structural health monitoring von Bull, L., Worden, K., Manson, G., Dervilis, N.

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On robust regression analysis as a means of exploring environmental and operational conditions for SHM data von Dervilis, N., Worden, K., Cross, E.J.

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Towards semi-supervised and probabilistic classification in structural health monitoring von Bull, L.A., Worden, K., Dervilis, N.

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On the application of kernelised Bayesian transfer learning to population-based structural health monitoring von Gardner, P., Bull, L.A., Dervilis, N., Worden, K.

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Foundations of Population-based SHM, Part II: Heterogeneous populations – Graphs, networks, and communities von Gosliga, J., Gardner, P.A., Bull, L.A., Dervilis, N., Worden, K.

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Equation discovery for nonlinear dynamical systems: A Bayesian viewpoint von Fuentes, R., Nayek, R., Gardner, P., Dervilis, N., Rogers, T., Worden, K., Cross, E.J.

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Overcoming the problem of repair in structural health monitoring: Metric-informed transfer learning von Gardner, P., Bull, L.A., Dervilis, N., Worden, K.

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Using Noncontact Measurement of Water Surface Dynamics to Estimate River Discharge von Dolcetti, G., Hortobágyi, B., Perks, M., Tait, S. J., Dervilis, N.

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Foundations of population-based SHM, Part I: Homogeneous populations and forms von Bull, L.A., Gardner, P.A., Gosliga, J., Rogers, T.J., Dervilis, N., Cross, E.J., Papatheou, E., Maguire, A.E., Campos, C., Worden, K.

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On the application of generative adversarial networks for nonlinear modal analysis von Tsialiamanis, G., Champneys, M.D., Dervilis, N., Wagg, D.J., Worden, K.

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On risk-based active learning for structural health monitoring von Hughes, A.J., Bull, L.A., Gardner, P., Barthorpe, R.J., Dervilis, N., Worden, K.

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Model selection and parameter estimation of dynamical systems using a novel variant of approximate Bayesian computation von Ben Abdessalem, A., Dervilis, N., Wagg, D., Worden, K.

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Machine learning at the interface of structural health monitoring and non-destructive evaluation von Gardner, P., Fuentes, R., Dervilis, N., Mineo, C., Pierce, S. G., Cross, E. J., Worden, K.

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A population-based SHM methodology for heterogeneous structures: Transferring damage localisation knowledge between different aircraft wings von Gardner, P., Bull, L.A., Gosliga, J., Poole, J., Dervilis, N., Worden, K.

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Feasibility study on a full‐scale wind turbine blade monitoring campaign: Comparing performance and robustness of features extracted from medium‐frequency active vibrations von Fremmelev, M. A., Ladpli, P., Orlowitz, E., Dervilis, N., McGugan, M., Branner, K.

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A probabilistic risk-based decision framework for structural health monitoring von Hughes, A.J., Barthorpe, R.J., Dervilis, N., Farrar, C.R., Worden, K.

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Foundations of population-based SHM, Part IV: The geometry of spaces of structures and their feature spaces von Tsialiamanis, G., Mylonas, C., Chatzi, E., Dervilis, N., Wagg, D.J., Worden, K.

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Probabilistic active learning: An online framework for structural health monitoring von Bull, L.A., Rogers, T.J., Wickramarachchi, C., Cross, E.J., Worden, K., Dervilis, N.

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Outlier ensembles: A robust method for damage detection and unsupervised feature extraction from high-dimensional data von Bull, L.A., Worden, K., Fuentes, R., Manson, G., Cross, E.J., Dervilis, N.

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