| CAFE: a computational tool for the study of gene family evolution T De Bie, N Cristianini, JP Demuth, MW Hahn Bioinformatics 22 (10), 1269-1271, 2006 | 1468 | 2006 |
| A statistical framework for genomic data fusion GRG Lanckriet, T De Bie, N Cristianini, MI Jordan, WS Noble Bioinformatics 20 (16), 2626-2635, 2004 | 914 | 2004 |
| FACE: feasible and actionable counterfactual explanations R Poyiadzi, K Sokol, R Santos-Rodriguez, T De Bie, P Flach Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 344-350, 2020 | 415 | 2020 |
| The evolution of mammalian gene families JP Demuth, TD Bie, JE Stajich, N Cristianini, MW Hahn PloS one 1 (1), e85, 2006 | 390 | 2006 |
| Flu detector-tracking epidemics on Twitter V Lampos, T De Bie, N Cristianini Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010 | 367 | 2010 |
| Estimating the tempo and mode of gene family evolution from comparative genomic data MW Hahn, T De Bie, JE Stajich, C Nguyen, N Cristianini Genome Research 15 (8), 1153-1160, 2005 | 334 | 2005 |
| Eigenproblems in pattern recognition T De Bie, N Cristianini, R Rosipal Handbook of Geometric Computing, 129-167, 2005 | 208* | 2005 |
| Kernel-based data fusion for gene prioritization T De Bie, LC Tranchevent, LMM van Oeffelen, Y Moreau Bioinformatics 23 (13), i125-i132, 2007 | 192 | 2007 |
| Maximum entropy models and subjective interestingness: an application to tiles in binary databases T De Bie Data Mining and Knowledge Discovery, 1-40, 2011 | 185 | 2011 |
| Convex methods for transduction T De Bie, N Cristianini Advances in neural information processing systems 16: proceedings of the …, 2004 | 168* | 2004 |
| Inferring transcriptional modules from ChIP-chip, motif and microarray data K Lemmens, T Dhollander, T De Bie, P Monsieurs, K Engelen, B Smets, ... Genome biology 7 (5), R37, 2006 | 136 | 2006 |
| Research methods in the age of digital journalism: Massive-scale automated analysis of news-content—topics, style and gender I Flaounas, O Ali, T Lansdall-Welfare, T De Bie, N Mosdell, J Lewis, ... Digital journalism 1 (1), 102-116, 2013 | 133* | 2013 |
| An information theoretic framework for data mining T De Bie Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 133 | 2011 |
| Automatic chord estimation from audio: A review of the state of the art M McVicar, R Santos-Rodríguez, Y Ni, T De Bie IEEE/ACM Transactions on Audio, Speech, and Language Processing 22 (2), 556-575, 2014 | 115 | 2014 |
| An end-to-end machine learning system for harmonic analysis of music Y Ni, M Mcvicar, R Santos-Rodriguez, T De Bie IEEE Transactions on Audio, Speech, and Language Processing 20 (6), 2012 | 100 | 2012 |
| Subjective interestingness in exploratory data mining T De Bie International Symposium on Intelligent Data Analysis, 19-31, 2013 | 85 | 2013 |
| Hit song science once again a science Y Ni, R Santos-Rodriguez, M Mcvicar, T De Bie 4th International Workshop on Machine Learning and Music, 2011 | 85 | 2011 |
| Debayes: a bayesian method for debiasing network embeddings M Buyl, T De Bie International Conference on Machine Learning, 1220-1229, 2020 | 81 | 2020 |
| MINI: Mining informative non-redundant itemsets A Gallo, T De Bie, N Cristianini Knowledge Discovery in Databases: PKDD 2007, 438-445, 2007 | 77 | 2007 |
| Semi-supervised learning using semi-definite programming T De Bie, N Cristianini Semi-supervised learning. MIT Press, Cambridge-Massachussets, 2006 | 77 | 2006 |
Nello CristianiniUniversity of BathVerified email at bath.ac.uk
