Dimensional complexity and spectral properties of the human sleep EEG Y Shen, E Olbrich, P Achermann, PF Meier Clinical Neurophysiology 114 (2), 199-209, 2003 | 133 | 2003 |

Variational inference for diffusion processes C Archambeau, M Opper, Y Shen, D Cornford, J Shawe-Taylor MIT, 2008 | 91 | 2008 |

Estimating the Hurst index of a self-similar process via the crossing tree OD Jones, Y Shen IEEE Signal Processing Letters 11 (4), 416-419, 2004 | 36 | 2004 |

Learning predictive statistics: strategies and brain mechanisms R Wang, Y Shen, P Tino, AE Welchman, Z Kourtzi Journal of Neuroscience 37 (35), 8412-8427, 2017 | 22 | 2017 |

Unravelling socio-motor biomarkers in schizophrenia P Słowiński, F Alderisio, C Zhai, Y Shen, P Tino, C Bortolon, ... npj Schizophrenia 3 (1), 1-10, 2017 | 22 | 2017 |

A comparison of variational and Markov chain Monte Carlo methods for inference in partially observed stochastic dynamic systems Y Shen, C Archambeau, D Cornford, M Opper, J Shawe-Taylor, R Barillec Journal of Signal Processing Systems 61 (1), 51-59, 2010 | 16 | 2010 |

An efficient algorithm to determine fractal dimensions of point sets RM Füchslin, Y Shen, PF Meier Physics Letters A 285 (1-2), 69-75, 2001 | 14 | 2001 |

Personalized medication response prediction for attention-deficit hyperactivity disorder: learning in the model space vs. learning in the data space HK Wong, PA Tiffin, MJ Chappell, TE Nichols, PR Welsh, OM Doyle, ... Frontiers in physiology 8, 199, 2017 | 11 | 2017 |

Functional brain networks for learning predictive statistics J Giorgio, VM Karlaftis, R Wang, Y Shen, P Tino, A Welchman, Z Kourtzi cortex 107, 204-219, 2018 | 9 | 2018 |

Spatial–temporal modelling of fMRI data through spatially regularized mixture of hidden process models Y Shen, SD Mayhew, Z Kourtzi, P Tiňo NeuroImage 84, 657-671, 2014 | 9 | 2014 |

Learning predictive statistics from temporal sequences: Dynamics and strategies R Wang, Y Shen, P Tino, AE Welchman, Z Kourtzi Journal of vision 17 (12), 1-1, 2017 | 8 | 2017 |

A new variational radial basis function approximation for inference in multivariate diffusions MD Vrettas, D Cornford, M Opper, Y Shen Neurocomputing 73 (7-9), 1186-1198, 2010 | 8 | 2010 |

Classifying cognitive profiles using machine learning with privileged information in mild cognitive impairment HH Alahmadi, Y Shen, S Fouad, CDB Luft, P Bentham, Z Kourtzi, P Tino Frontiers in computational neuroscience 10, 117, 2016 | 7 | 2016 |

Advances in Neural Information Processing Systems 20 C Archambeau, M Opper, Y Shen, D Cornford, J Shawe-Taylor, J Platt, ... MIT Press, 2008 | 7 | 2008 |

Analyzing self-similarity in network traffic via the crossing tree OD Jones, Y Shen Online preprint available from: www. maths. soton. ac. uk/staff/ODJones …, 2003 | 6 | 2003 |

Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions Y Shen, D Cornford, M Opper, C Archambeau Computational Statistics 27 (1), 149-176, 2012 | 5 | 2012 |

A variational basis function approximation for diffusion processes M Vrettas, D Cornford, Y Shen Proceedings of the 17th European Symposium on Artificial Neural Networks …, 2009 | 5 | 2009 |

Classification framework for partially observed dynamical systems Y Shen, P Tino, K Tsaneva-Atanasova Physical Review E 95 (4), 043303, 2017 | 4 | 2017 |

Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning VM Karlaftis, J Giorgio, PE Vértes, R Wang, Y Shen, P Tino, AE Welchman, ... Nature human behaviour 3 (3), 297-307, 2019 | 3 | 2019 |

A non-parametric test for self-similarity and stationarity in network traffic OD Jones, Y Shen Fractals in Engineering, 219-234, 2005 | 3 | 2005 |