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A new methodology for automating acoustic emission detection of metallic fatigue fractures in highly demanding aerospace environments: an overviewHolford, K.M., Eaton, M.J., Hensman, J.J., Pullin, R., Evans, S.L., Dervilis, N., Worden, K. 6/01/2017 In: Progress in Aerospace Sciences. Detecting periodicities with Gaussian processesDurrande, N., Hensman, J., Rattray, M., Lawrence, N.D. 13/04/2016 In: PeerJ Computer Science. 2 On sparse variational methods and the Kullback-Leibler divergence between stochastic processesMatthews, A.G.d.G., Hensman, J., Turner, R., Ghahramani, Z. 4/01/2016 In: Journal of Machine Learning Research. 51, p. 231-239. 9 p. Fast and accurate approximate inference of transcript expression from RNA-seq dataHensman, J., Papastamoulis, P., Glaus, P., Honkela, A., Rattray, M. 15/12/2015 In: Bioinformatics. 31, 24, p. 3881-3889. 9 p. Damage localisation in delaminated composite plates using a Gaussian process approachCorrado, N., Gherlone, M., Surace, C., Hensman, J., Durrande, N. 10/2015 In: Meccanica. 50, 10, p. 2537-2546. 10 p. Hoxa2 selectively enhances meis binding to change a branchial arch ground stateAmin, S., Donaldson, I.J., Zannino, D.A., Hensman, J., Rattray, M., Losa, M., Spitz, F., Ladam, F., Sagerstr?m, C., Bobola, N. 9/02/2015 In: Developmental Cell. 32, 3, p. 265-277. 13 p. Fast nonparametric clustering of structured time-seriesHensman, J., Rattray, M., Lawrence, N.D. 1/02/2015 In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 37, 2, p. 383-393. 11 p. Scalable variational Gaussian process classificationHensman, J., Matthews, A.G., Ghahramani, Z. 02/2015 In: JMLR: Workshop and Conference Proceedings. 38, p. 351-360. 10 p. MCMC for variationally sparse Gaussian processesHensman, J., De Matthews, A.G., Filippone, M., Ghahramani, Z. 2015 In: Advances in Neural Information Processing Systems. Neural information processing systems foundation p. 1648-1656. 9 p. Gremlin-2 is a BMP antagonist that is regulated by the circadian clockYeung, C.Y.C., Gossan, N., Lu, Y., Hughes, A., Hensman, J.J., Bayer, M.L., Kj?r, M., Kadler, K.E., Meng, Q.J. 5/06/2014 In: Scientific Reports. 4 Improved variational Bayes inference for transcript expression estimationPapastamoulis, P., Hensman, J., Glaus, P., Rattray, M. 04/2014 In: Statistical Applications in Genetics and Molecular Biology. 13, 2, p. 203-216. 14 p. A Gaussian process approach to locate cracks in plate-like structuresSurace, C., Hensman, J., Mattone, M., Gherlone, M., Corrado, N. 2014 In: Proceedings of the Twelfth International Conference on Computational Structures Technology. Hybrid discriminative-generative approach with Gaussian processesAndrade-Pacheco, R., Hensman, J., Zwie?ele, M., Lawrence, N.D. 2014 In: JMLR: Workshop and Conference Proceedings. 33, p. 47-56. 10 p. Tilted variational bayesHensman, J., Zwie?ele, M., Lawrence, N.D. 2014 In: JMLR: Workshop and Conference Proceedings. 33, p. 356-364. 9 p. The circadian clock in murine chondrocytes regulates genes controlling key aspects of cartilage homeostasisGossan, N., Zeef, L., Hensman, J., Hughes, A., Bateman, J.F., Rowley, L., Little, C.B., Piggins, H.D., Rattray, M., Boot-Handford, R.P., Meng, Q.J. 09/2013 In: Arthritis and Rheumatism. 65, 9, p. 2334-2345. 12 p. Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clustersHensman, J., Lawrence, N.D., Rattray, M. 20/08/2013 In: BMC Bioinformatics. 14, 1, 12 p. Parameter estimation and model selection for a class of hysteretic systems using Bayesian inferenceWorden, K., Hensman, J.J. 10/2012 In: Mechanical Systems and Signal Processing. 32, p. 153-169. 17 p. Genome-wide occupancy links Hoxa2 to Wnt-β-catenin signaling in mouse embryonic developmentDonaldson, I.J., Amin, S., Hensman, J.J., Kutejova, E., Rattray, M., Lawrence, N., Hayes, A., Ward, C.M., Bobola, N. 05/2012 In: Nucleic Acids Research. 40, 9, p. 3990-4001. 12 p. Albumin level and patient age predict outcomes in patients referred for gastrostomy insertion: internal and external validation of a gastrostomy score and comparison with artificial neural networksLeeds, J., McAlindon, M.E., Grant, J., Robson, H.E., Morley, S.R., James, G., Hoeroldt, B., Kapur, K., Dear, K., Hensman, J., Worden, K., Sanders, D.S. 11/2011 In: Gastrointestinal Endoscopy. 74, 5, p. 1033-1039. 7 p. Spatial scanning for anomaly detection in acoustic emission testing of an aerospace structureHensman, J., Worden, K., Eaton, M., Pullin, R., Holford, K., Evans, S. 10/2011 In: Mechanical Systems and Signal Processing. 25, 7, p. 2462-2474. 13 p. Principal component analysis of acoustic emission signals from landing gear components: an aid to fatigue fracture detectionEaton, M.J., Pullin, R., Hensman, J.J., Holford, K.M., Worden, K., Evans, S.L. 06/2011 In: Strain. 47, SUPPL. 1, p. e588-e594. 7 p. Natural computing for mechanical systems research: a tutorial overviewWorden, K., Staszewski, W.J., Hensman, J.J. 01/2011 In: Mechanical Systems and Signal Processing. 25, 1, p. 4-111. 108 p. Detecting mode-shape discontinuities without differentiation: examining a Gaussian process approachHensman, J., Surace, C., Gherlone, M. 2011 In: Journal of Physics: Conference Series. 305, 1 Locating acoustic emission sources in complex structures using Gaussian processesHensman, J., Mills, R., Pierce, S.G., Worden, K., Eaton, M. 01/2010 In: Mechanical Systems and Signal Processing. 24, 1, p. 211-223. 13 p. Acoustic emission for monitoring aircraft structuresHolford, K.M., Pullin, R., Evans, S.L., Eaton, M.J., Hensman, J., Worden, K. 05/2009 In: Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering. 223, 5, p. 525-532. 8 p.