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Article

Pararasa, Chathyan; Ikwuobe, John; Shigdar, Shahjahan; Boukouvalas, Alexis; Nabney, Ian T.; Brown, James E.; Devitt, Andrew; Bailey, Clifford J.; Bennett, Stuart J. and Griffiths, Helen R. (2016). Age-associated changes in long-chain fatty acid profile during healthy aging promote pro-inflammatory monocyte polarization via PPARγ. Aging Cell, 15 (1), pp. 128-139.

Chen, Niya; Qian, Zheng; Nabney, Ian T. and Meng, Xiaofeng (2014). Wind power forecasts using Gaussian processes and numerical weather prediction. IEEE Transactions on Power Systems, 29 (2), pp. 656-665.

Maciol, Ryszard; Yuan, Yuan and Nabney, Ian T. (2011). Colour image coding with matching pursuit in the spatio-frequency domain. Lecture Notes in Computer Science, 6978 , pp. 306-317.

Maniyar, Dharmesh M.; Nabney, Ian T.; Williams, Bruce S. and Sewing, Andreas (2006). Data visualization during the early stages of drug discovery. Journal of Chemical Information and Modeling, 46 (4), pp. 1806-1818.

Maniyar, Dharmesh M. and Nabney, Ian T. (2005). Guiding local regression using visualisation. Lecture notes in computer science, 3635/2 , pp. 98-109.

Nabney, Ian T.; Sun, Yi; Tiňo, Peter and Kabán, Ata (2005). Semisupervised learning of hierarchical latent trait models for data visualization. IEEE Transactions on Knowledge and Data Engineering, 17 (3), pp. 384-400.

Nabney, Ian T. (2004). Efficient training of RBF networks for classification. International Journal of Neural Systems, 14 (3), pp. 201-208.

Bullen, Robert; Cornford, Dan and Nabney, Ian T. (2003). Outlier detection in scatterometer data:Neural network approaches. Neural Networks, 16 (3-4), pp. 419-426.

Tino, Peter and Nabney, Ian T. (2002). Hierarchical GTM: constructing localized non-linear projection manifolds in a principled way. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24 (5), pp. 639-656.

Azzouzi, M and Nabney, Ian T. (2001). Dynamical local models for segmentation and prediction of financial time series. European Journal of Finance, 7 (4), pp. 289-311.

Evans, David J.; Cornford, Dan and Nabney, Ian T. (2000). Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements. Neurocomputing, 30 (1-4), pp. 23-30.

Cornford, Dan; Nabney, Ian T. and Bishop, Christopher M. (1999). Neural network-based wind vector retrieval from satellite scatterometer data. Neural Computing and Applications, 8 (3), pp. 206-217.

Cornford, Dan; Nabney, Ian T. and Williams, Christopher K. I. (1999). Adding constrained discontinuities to Gaussian process models of wind fields. Advances in Neural Information Processing Systems, 11 , pp. 861-867.

Bishop, Christopher M. and Nabney, Ian T. (1996). Modelling conditional probability distributions for periodic variables. Neural Computation, 8 (5), pp. 209-214.

Nabney, Ian T.; Dunis, Christian; Dallaway, Richard; Leong, Swee and Redshaw, Wendy (1995). Leading edge forecasting techniques for exchange rate prediction. European Journal of Finance, 1 (4), pp. 311-323.

Nabney, Ian T.; Cornford, Dan and Williams, Christopher K. I. Bayesian inference for wind field retrieval. Neurocomputing, 30 (1-4), pp. 3-11.

Marcos, J.V.; Homero, R.; Álvarez, D.; Nabney, Ian T.; del Campo, F. and Zamarron, C. Classification of oximetry signals using Bayesian neural networks to assist in the detection of obstructive sleep apnoea syndrome. Physiological Measurement, 31 (3), pp. 375-394.

Cornford, Dan; Nabney, Ian T. and Ramage, Guillaume Improved neural network scatterometer forward models. Journal of Geophysical Research, 106 (C10), pp. 22331-22338.

López-Vallejo, Fabian; Nefzi, Adel; Bender, Andreas; Owen, John R.; Nabney, Ian T.; Houghten, Richard A. and Medina-Franco, Jose L. Medina Increased diversity of libraries from libraries: chemoinformatic analysis of bis-diazacyclic libraries. Chemical Biology and Drug Design, 77 (5), pp. 328-342.

Cornford, Dan; Nabney, Ian T. and Williams, Christopher K. I. Modelling frontal discontinuities in wind fields. Journal of Nonparametric Statistics, 14 (1-2), pp. 43-58.

Cressy, D.C.; Nabney, Ian T. and Simper, A. Neural control of a batch distillation. Neural Computing and Applications, 1 (2), pp. 115-123.

Cornford, Dan; Wright, W.A.; Ramage, Guillaume and Nabney, Ian T. Neural network modelling with input uncertainty:theory and application. Journal of VLSI Signal Processing Systems for Signal Image and Video Technology, 26 (1-2), pp. 169-188.

Bunkute, Egle; Cummins, Christopher; Crofts, Fraser; Bunce, Gareth; Nabney, Ian T. and Flower, Darren R. PIP-DB:the protein isoelectric point database. Bioinformatics, 31 (2), pp. 295-296.

Marcos, J. Víctor; Hornero, Roberto; Nabney, Ian T.; Álvarez, Daniel; Gutiérrez-Tobal, Gonzalo C. and del Campo, Félix Regularity analysis of nocturnal oximetry recordings to assist in the diagnosis of sleep apnoea syndrome. Medical Engineering and Physics, 38 (3), pp. 216-224.

Nguyen, Hang T.; Nabney, Ian T. and , Non-linearity and Complexity Research Group, School of Engineeri Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models. Energy, 35 (9), pp. 3674-3685.

Thi-hang, Nguyen and Nabney, Ian T. Variational inference for Student-t MLP models. Neurocomputing, 73 (16-18), pp. 2989-2997.

Owen, John R.; Nabney, Ian T.; Medina-Franco, José L. and López-Vallejo, Fabian Visualization of molecular fingerprints. Journal of Chemical Information and Modeling, 51 (7), pp. 1552-1563.

West, Ansgar H. L.; Saad, David and Nabney, Ian T. The learning dynamics of a universal approximator. Advances in Neural Information Processing Systems, 9 , pp. 288-294.

Cornford, Dan; Ramage, Guillaume and Nabney, Ian T. A scatterometer neural network sensor model with input noise. Neurocomputing, 30 (1), pp. 13-21.

Book Section

Almeida, Vania G. and Nabney, Ian T. (2017). Detecting dynamical changes in vital signs using switching Kalman filter. IN: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017. IEEE.

Almeida, Vânia G. and Nabney, Ian T. (2016). Early warnings of heart rate deterioration. IN: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016. IEEE.

Gill, Waljinder S.; Nabney, Ian T. and Wells, Daniel (2013). Inference of helicopter airframe condition. IN: 2013 IEEE International Workshop on Machine Learning for Signal Processing September 22-25, Southampton, United Kingdom. Proceedings MLSP2013. Sanei, Saeid; Smaragdis, Paris; Nandi, Asoke and et al, (eds) Machine learning for signal processing . IEEE.

Chen, Niya; Qian, Zheng; Meng, Xiaofeng and Nabney, Ian T. (2013). Short-term wind power forecasting using Gaussian processes. IN: Proceedings of the twenty-third International Joint Conference on Artificial Intelligence. AAAI.

Nguyen, Hang T. and Nabney, Ian T. (2009). Energy forward price prediction with a hybrid adaptive model. IN: IEEE Symposium on Computational Intelligence for Financial Engineering, 2009. CIFEr '09. IEEE.

Maniyar, Dharmesh M. and Nabney, Ian T. (2006). Visual data mining using principled projection algorithms and information visualization techniques. IN: Proceedings of the Twelfth ACM SIGKDD international conference on knowledge discovery and data mining. New York (US): ACM.

Hjorth, Lars U. and Nabney, Ian T. (2000). Bayesian training of mixture density networks. IN: Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000. IJCNN 2000. Piscataway, NJ, United States: IEEE.

Nabney, Ian T.; Paven, Mickael J S; Eldridge, Richard C and Lee, Clive (1997). Practical assessment of neural network applications. IN: SafeComp 97: Proceedings of the 16th International Conference on Computing Safety, Reliability and Security. Daniel, Peter (ed.) London: Springer.

Nabney, Ian T.; McLachlan, Alan and Lowe, David (1996). Practical methods of tracking of nonstationary time series applied to real-world data. IN: Applications and science of artificial neural networks II. Rogers, S.K. and Ruck, D.W. (eds) SPIE proceedings, 2760 . SPIE.

Nabney, Ian T. and Grasl, O. (1991). Rule induction for data exploration. IN: Proceedings of Avignon 91: Expert systems and their applications. EC2 et Cie.

Azzouzi, Mehdi and Nabney, Ian T. Analysing time series structure with hidden Markov models. IN: Proceedings of the 1998 IEEE Signal Processing Society Workshop, Neural Networks for Signal Processing VIII, 1998. Constantinides, Tony; Kung, S. Y.; Niranjan, Mahesan and Wilson, Elizabeth (eds) Proceedings of the 1998 IEEE Signal Processing Society Workshop, 8 . Cambridge, UK: IEEE.

Marcos, J. Victor; Hornero, Roberto; Nabney, Ian T.; Álvarez, Daniel and del Campo, Félix Analysis of nocturnal oxygen saturation recordings using kernel entropy to assist in sleep apnea-hypopnea diagnosis. IN: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC, 2011. Conference proceedings IEEE Engineering in Medicine and Biology Society . IEEE.

Nguyen, Hang T. and Nabney, Ian T. Combining the wavelet transform and forecasting models to predict gas forward prices. IN: Seventh International Conference on Machine Learning and Applications, 2008. ICMLA '08. IEEE.

Cornford, Dan; Schroeder, Martin and Nabney, Ian T. Data visualisation and exploration with prior knowledge. IN: Engineering applications of neural networks. Communications in computer and information science, 43 CCI . Beriln (DE): Springer.

Maniyar, Dharmesh M. and Nabney, Ian T. Data visualization with simultaneous feature selection. IN: Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06. UNSPECIFIED.

Nabney, Ian T.; Evans, David J.; Brule, Yann and Gordon, Caroline Evaluating the effectiveness of Bayesian feature selection. IN: Applications of probabilistic modelling in medical informatics and bioinformatics. Dybowski, R.; Husmeier, D. and Roberts, S. J. (eds) Advanced information and knowledge processing . Springer.

Maniyar, Dharmesh M. and Nabney, Ian T. Guiding local regression using visualisation. IN: Deterministic and statistical methods in machine learning. Winkler, Joab; Niranjan, Mahesan and Lawrence, Neil (eds) Lecture Notes in Computer Science . Berlin (DE): Springer.

Gill, Waljinder S.; Nabney, Ian T. and Wells, D. Helicopter vibration sensor selection using data visualisation. IN: IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012. Machine learning for signal processing . IEEE.

Nabney, Ian T.; Bishop, Christopher M. and Legleye, C. Modelling conditional probability distributions for periodic variables. IN: Fourth International Conference on Artificial Neural Networks. IEEE.

Azzouzi, Mehdi and Nabney, Ian T. Modelling financial time series with switching state space models. IN: Proceedings of the IEEE/IAFE 1999 Conference on Computational Intelligence for Financial Engineering. Port Jefferson, NY: IEEE.

Woodcock, D. and Nabney, Ian T. Prediction of paroxysmal atrial fibrillation. IN: Proceedings of the 2nd International Conference on Computational Intelligence in Medicine and Healthcare (CIMED2005). Plymouth: BIOPATTERN Network of Excellence.

Hjorth, Lars U. and Nabney, Ian T. Regularisation of mixture density networks. IN: Ninth International Conference on Artificial Neural Networks, 1999. IET conference publications, 2 . IET.

Azzouzi, Mehdi and Nabney, Ian T. Time delay estimation with hidden Markov models. IN: Ninth International Conference on Artificial Neural Networks, 1999 (ICANN). Edinburgh, UK: IEEE.

Tino, Peter; Nabney, Ian T. and Sun, Yi Using directional curvatures to visualize folding patterns of the GTM projection manifolds. IN: Artificial Neural Networks — ICANN 2001. Dorffner, G.; Bischof, H. and Hornik., K. (eds) Lecture Notes in Computer Science, 2130 . Springer.

Mumtaz, Shahzad; Randrianandrasana, Michel F.; Bassi, Gurjinder and Nabney, Ian T. Visualisation of heterogeneous data with simultaneous feature saliency using Generalised Generative Topographic Mapping. IN: Workshop new challenges in neural computation 2015. Hammer, Barbara; Martinetz, Thomas and Villmann, Thomas (eds) Machine learning reports . Bielefeld (DE): Universität Bielefeld.

Monograph

Schroeder, Martin; Nabney, Ian T. and Cornford, Dan (2008). Block GTM: Incorporating prior knowledge of covariance structure in data visualisation. Technical Report. Aston University, Birmingham.

Maniyar, Dharmesh M. and Nabney, Ian T. (2005). EM algorithm for GTM-FS. Technical Report. Aston University, Birmingham.

Cornford, Dan; Nabney, Ian T. and Evans, David J. (1999). Bayesian retrieval of scatterometer wind fields. Technical Report. Aston University, Birmingham. (Unpublished)

Cornford, Dan; Nabney, Ian T.; Williams, Christopher K. I.; Kearns, Michael S.; Solla, Sara A. and Cohn, David A. (1998). Adding constrained discontinuities to Gaussian process models of wind fields. Technical Report. Aston University, Birmingham.

Evans, David J.; Cornford, Dan and Nabney, Ian T. (1998). Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements. Technical Report. Aston University, Birmingham.

Cornford, Dan; Ramage, Guillaume and Nabney, Ian T. (1998). A scatterometer neural network sensor model with input noise. Technical Report. Aston University, Birmingham.

Nabney, Ian T. and Bishop, Christopher M. (1995). Modelling wind direction from satellite scatterometer data. Technical Report. Aston University, Birmingham.

Cornford, Dan; Nabney, Ian T. and Williams, Christopher K. I. Bayesian inference for wind field retrieval. Technical Report. Aston University, Birmingham.

Maniyar, Dharmesh M. and Nabney, Ian T. DVMS 1.5: A user manual (the data visualization and modeling system). Manual. Aston University, Birmingham.

Azzouzi, Mehdi and Nabney, Ian T. Delay estimation for multivariate time series. Technical Report. Aston University, Aston University, Birmingham, UK.

Sun, Yi; Tino, Peter and Nabney, Ian T. GTM-based data visualisation with incomplete data. Technical Report. Aston University, Birmingham, UK. (Unpublished)

Cornford, Dan; Nabney, Ian T. and Ramage, Guillaume Improved multi-beam neural network scatterometer forward models. Technical Report. Aston University, Birmingham, UK.

Cornford, Dan and Nabney, Ian T. NEUROSAT: an overview. Technical Report. Aston University, Birmingham.

Cornford, Dan; Nabney, Ian T. and Bishop, Christopher M. Neural network-based wind vector retrieval from satellite scatterometer data. Technical Report. Aston University, Birmingham.

Hjorth, Lars U. and Nabney, Ian T. Regularised mixture density networks for modelling wind direction. Technical Report. Neural Computation Research Group, Birmingham.

Sun, Yi; Tino, Peter; Kaban, Ata and Nabney, Ian T. Semi-supervised learning of hierarchical latent trait models for data visualisation. Technical Report. Aston University, Birmingham, UK.

Woodcock, D. and Nabney, Ian T. A new entropy measure based on the Renyi entropy rate using Gaussian kernels. Technical Report. Aston University, Birmingham.

Conference or Workshop Item

Tino, Peter; Sun, Yi and Nabney, Ian T. (2002). Semi-supervised construction of general visualization hierarchies. IN: International Conference on Artificial Intelligence, 2002. 2002-01-01 - 2002-01-01.

Nabney, Ian T. and Cheng, H. W. (1997). Estimating conditional volatility with neural networks. IN: Fourth Internation Conference: Forecasting Financial Markets. 1997-01-01 - 1997-01-01.

Nabney, Ian T. Efficient training of RBF networks for classification. IN: 9th International Conference on Artificial Neural Networks. 1999-09-07 - 1999-09-07.

Tino, Peter; Nabney, Ian T.; Sun, Yi and Williams, Bruce S. A principled approach to interactive hierarchical non-linear visualization of high-dimensional data. IN: Interface '01 - Frontiers in Data Mining and Bioinformatics. 2002-01-01 - 2002-01-01. (Submitted)