Random-walk computation of similarities between nodes of a graph with application to collaborative recommendation F Fouss, A Pirotte, JM Renders, M Saerens IEEE Transactions on knowledge and data engineering 19 (3), 355-369, 2007 | 1689 | 2007 |

Adjusting the Outputs of a Classifier to New a *Priori* Probabilities: A Simple ProcedureM Saerens, P Latinne, C Decaestecker Neural computation 14 (1), 21-41, 2002 | 466 | 2002 |

The principal components analysis of a graph, and its relationships to spectral clustering M Saerens, F Fouss, L Yen, P Dupont Machine Learning: ECML 2004: 15th European Conference on Machine Learning …, 2004 | 339 | 2004 |

Neural controller based on back-propagation algorithm M Saerens, A Soquet IEE Proceedings F (Radar and Signal Processing) 138 (1), 55-62, 1991 | 205* | 1991 |

An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification F Fouss, K Francoisse, L Yen, A Pirotte, M Saerens Neural networks 31, 53-72, 2012 | 187 | 2012 |

Predicting the *continuum* between corridors and barriers to animal movements using Step Selection Functions and Randomized Shortest PathsM Panzacchi, B Van Moorter, O Strand, M Saerens, I Kivimäki, ... Journal of Animal Ecology 85 (1), 32-42, 2016 | 160 | 2016 |

A novel way of computing similarities between nodes of a graph, with application to collaborative recommendation F Fouss, A Pirotte, M Saerens The 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI'05 …, 2005 | 152 | 2005 |

An experimental investigation of graph kernels on a collaborative recommendation task F Fouss, L Yen, A Pirotte, M Saerens Sixth International Conference on Data Mining (ICDM'06), 863-868, 2006 | 150 | 2006 |

Algorithms and models for network data and link analysis F Fouss, M Saerens, M Shimbo Cambridge University Press, 2016 | 144 | 2016 |

Randomized shortest-path problems: Two related models M Saerens, Y Achbany, F Fouss, L Yen Neural computation 21 (8), 2363-2404, 2009 | 140 | 2009 |

clustering using a random walk based distance measure. L Yen, D Vanvyve, F Wouters, F Fouss, M Verleysen, M Saerens ESANN, 317-324, 2005 | 139 | 2005 |

A family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances L Yen, M Saerens, A Mantrach, M Shimbo Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 126 | 2008 |

A neural controller M Saerens, A Soquet 1989 First IEE International Conference on Artificial Neural Networks,(Conf …, 1989 | 124 | 1989 |

Graph nodes clustering with the sigmoid commute-time kernel: A comparative study L Yen, F Fouss, C Decaestecker, P Francq, M Saerens Data & Knowledge Engineering 68 (3), 338-361, 2009 | 112 | 2009 |

Graph nodes clustering based on the commute-time kernel L Yen, F Fouss, C Decaestecker, P Francq, M Saerens Pacific-Asia Conference on Knowledge Discovery and Data Mining, 1037-1045, 2007 | 108 | 2007 |

Developments in the theory of randomized shortest paths with a comparison of graph node distances I Kivimäki, M Shimbo, M Saerens Physica A: Statistical Mechanics and its Applications 393, 600-616, 2014 | 106 | 2014 |

A time-based collective factorization for topic discovery and monitoring in news CK Vaca, A Mantrach, A Jaimes, M Saerens Proceedings of the 23rd international conference on World wide web, 527-538, 2014 | 95 | 2014 |

The sum-over-paths covariance kernel: A novel covariance measure between nodes of a directed graph A Mantrach, L Yen, J Callut, K Francoisse, M Shimbo, M Saerens IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (6), 1112-1126, 2009 | 85 | 2009 |

Two betweenness centrality measures based on randomized shortest paths I Kivimäki, B Lebichot, J Saramäki, M Saerens Scientific reports 6 (1), 19668, 2016 | 76 | 2016 |

Building cost functions minimizing to some summary statistics M Saerens IEEE Transactions on neural networks 11 (6), 1263-1271, 2000 | 72 | 2000 |