| Gene networks inference using dynamic Bayesian networks BE Perrin, L Ralaivola, A Mazurie, S Bottani, J Mallet, F d’Alche–Buc Bioinformatics 19 (suppl_2), ii138-ii148, 2003 | 578 | 2003 |
| Estimating parameters and hidden variables in nonlinear state-space models based on ODEs for biological networks M. Quach, N Brunel, F d'Alché-Buc Bioinformatics 23 (23), 3209-3216, 2007 | 188 | 2007 |
| Support vector machines based on a semantic kernel for text categorization G Siolas, F d'Alché-Buc Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural …, 2000 | 185 | 2000 |
| Incremental support vector machine learning: A local approach L Ralaivola, F d’Alché-Buc International conference on artificial neural networks, 322-330, 2001 | 156 | 2001 |
| Improving reproducibility in machine learning research: a report from the NeurIPS 2019 reproducibility program J Pineau, P Vincent-Lamarre, K Sinha, V Larivière, A Beygelzimer, ... Journal of Machine Learning Research 22, 2021 | 117 | 2021 |
| Semi-supervised marginboost F d'Alché-Buc, Y Grandvalet, C Ambroise Advances in neural information processing systems, 553-560, 2001 | 117 | 2001 |
| Autoregressive models for gene regulatory network inference: Sparsity, stability and causality issues G Michailidis, F d’Alché-Buc Mathematical biosciences 246 (2), 326-334, 2013 | 90 | 2013 |
| Semi-supervised penalized output kernel regression for link prediction C Brouard, F d'Alché-Buc, M Szafranski Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011 | 82 | 2011 |
| Dynamical modeling with kernels for nonlinear time series prediction L Ralaivola, F d'Alche-Buc Advances in neural information processing systems 16, 129, 2004 | 73 | 2004 |
| RAR/RXR binding dynamics distinguish pluripotency from differentiation associated cis-regulatory elements B Chatagnon, Veber, Morin, Bedo, Triqueneaux, Sémon, Laudet, d'Alché-Buc Nucleic Acids Research 43 (10), 4833-4854, 2015 | 71 | 2015 |
| Time series filtering, smoothing and learning using the kernel Kalman filter L Ralaivola, F d'Alché-Buc Proceedings. 2005 IEEE International Joint Conference on Neural Networks …, 2005 | 71 | 2005 |
| Fast metabolite identification with input output kernel regression C Brouard, H Shen, K Dührkop, F d'Alché-Buc, S Böcker, J Rousu Bioinformatics 32 (12), i28-i36, 2016 | 68 | 2016 |
| Kernelizing the output of tree-based methods P Geurts, L Wehenkel, F d'Alché-Buc Proceedings of the 23rd international conference on Machine learning, 345-352, 2006 | 68 | 2006 |
| Input output kernel regression: Supervised and semi-supervised structured output prediction with operator-valued kernels C Brouard, M Szafranski, F d’Alché-Buc Journal of Machine Learning Research 17 (176), 1-48, 2016 | 54 | 2016 |
| Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset C Auliac, V Frouin, X Gidrol, F d'Alché-Buc BMC bioinformatics 9 (1), 1-14, 2008 | 54 | 2008 |
| Inferring biological networks with output kernel trees P Geurts, N Touleimat, M Dutreix, F d'Alché-Buc BMC bioinformatics 8 (2), 1-12, 2007 | 54 | 2007 |
| Operator-valued kernel-based vector autoregressive models for network inference N Lim, F d’Alché-Buc, C Auliac, G Michailidis Machine learning 99 (3), 489-513, 2015 | 48 | 2015 |
| System monitoring the discharging period of the charging/discharging cycles of a rechargeable battery, and host device including a smart battery JN Patillon, F D'Alche-Buc, JP Nadal US Patent 5,936,385, 1999 | 48 | 1999 |
| Confidence measures for neural network classifiers H Zaragoza, F d’Alché-Buc Proceedings of the Seventh Int. Conf. Information Processing and Management …, 1998 | 38 | 1998 |
| Flexible and context-specific AI explainability: A multidisciplinary approach V Beaudouin, I Bloch, D Bounie, S Clémençon, F d'Alché-Buc, J Eagan, ... arXiv preprint arXiv:2003.07703, 2020 | 37 | 2020 |
Liva RalaivolaCriteo AI LabVerified email at criteo.com
