Maurizio Filippone

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Citations	4829	2995
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Pietro MichiardiEURECOMVerified email at eurecom.fr
Edwin V. BonillaPrincipal Research Scientist, CSIRO's Data61Verified email at data61.csiro.au
Mark GirolamiUniversity of CambridgeVerified email at cam.ac.uk
Dimitrios MiliosPost Doctoral Fellow, EURECOMVerified email at eurecom.fr
Simone RossiAssistant Professor, EURECOMVerified email at eurecom.fr
Kurt CutajarAmazonVerified email at amazon.com
Simon RogersSenior Lecturer, Computing Science, University of GlasgowVerified email at glasgow.ac.uk
Ba-Hien TranHuawei Paris Research CenterVerified email at huawei.com
Marco LorenziUniversité Côte d'Azur, InriaVerified email at inria.fr
Giulio FranzeseAssistant Professor - EurecomVerified email at eurecom.fr
Michael A OsborneProfessor of Machine Learning, University of OxfordVerified email at robots.ox.ac.uk
Alessandro VinciarelliFull Professor at University of Glasgow - School of Computing ScienceVerified email at dcs.gla.ac.uk
Markus HeinonenAcademy research Fellow, Aalto UniversityVerified email at aalto.fi
Guido SanguinettiReader in Informatics, University of EdinburghVerified email at inf.ed.ac.uk
John CunninghamProfessor, Columbia UniversityVerified email at columbia.edu
James HensmanMicrosoft ResearchVerified email at microsoft.com
Andre F MarquandProfessor of Computational Psychiatry, Donders Institute / Kings College LondonVerified email at kcl.ac.uk
Matteo Dell'AmicoUniversity of GenoaVerified email at unige.it
Alexander G. D. G. MatthewsDeepMindVerified email at google.com
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk

Maurizio Filippone

Associate Professor - Statistics Program, KAUST

Verified email at kaust.edu.sa - Homepage

Bayesian Deep Learning Gaussian Processes Bayesian Inference Computational Statistics


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A survey of kernel and spectral methods for clustering M Filippone, F Camastra, F Masulli, S Rovetta Pattern recognition 41 (1), 176-190, 2008	1112	2008
A comparative evaluation of outlier detection algorithms: Experiments and analyses R Domingues, M Filippone, P Michiardi, J Zouaoui Pattern recognition 74, 406-421, 2018	553	2018
Random feature expansions for deep Gaussian processes K Cutajar, EV Bonilla, P Michiardi, M Filippone Proceedings of the 35th International Conference on Machine Learning 70, 884 …, 2017	188	2017
MCMC for variationally sparse Gaussian processes J Hensman, AG Matthews, M Filippone, Z Ghahramani Advances in neural information processing systems 28, 2015	170	2015
Aggregation algorithm towards large-scale Boolean network analysis Y Zhao, J Kim, M Filippone IEEE Transactions on Automatic Control 58 (8), 1976-1985, 2013	158	2013
ODE parameter inference using adaptive gradient matching with Gaussian processes F Dondelinger, D Husmeier, S Rogers, M Filippone Artificial intelligence and statistics, 216-228, 2013	156	2013
Probabilistic disease progression modeling to characterize diagnostic uncertainty: application to staging and prediction in Alzheimer's disease M Lorenzi, M Filippone, GB Frisoni, DC Alexander, S Ourselin, ... NeuroImage 190, 56-68, 2019	133	2019
Monte Carlo strength evaluation: Fast and reliable password checking M Dell'Amico, M Filippone Proceedings of the 22nd ACM SIGSAC conference on computer and communications …, 2015	121	2015
Decoding post-stroke motor function from structural brain imaging JM Rondina, M Filippone, M Girolami, NS Ward NeuroImage: Clinical 12, 372-380, 2016	105	2016
Dirichlet-based gaussian processes for large-scale calibrated classification D Milios, R Camoriano, P Michiardi, L Rosasco, M Filippone Advances in Neural Information Processing Systems 31, 2018	97	2018
Preconditioning kernel matrices K Cutajar, MA Osborne, JP Cunningham, M Filippone Proceedings of the 33rd International Conference on Machine Learning, 2529-2538, 2016	95	2016
Pseudo-marginal Bayesian inference for Gaussian processes M Filippone, M Girolami IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (11), 2214 …, 2014	81	2014
All you need is a good functional prior for Bayesian deep learning BH Tran, S Rossi, D Milios, M Filippone Journal of Machine Learning Research 23 (74), 1-56, 2022	80	2022
Deep compositional spatial models A Zammit-Mangion, TLJ Ng, Q Vu, M Filippone Journal of the American Statistical Association 117 (540), 1787-1808, 2022	72	2022
A comparative evaluation of stochastic-based inference methods for Gaussian process models M Filippone, M Zhong, M Girolami Machine Learning 93, 93-114, 2013	71	2013
AutoGP: Exploring the capabilities and limitations of Gaussian process models K Krauth, EV Bonilla, K Cutajar, M Filippone arXiv preprint arXiv:1610.05392, 2016	67	2016
Information theoretic novelty detection M Filippone, G Sanguinetti Pattern Recognition 43 (3), 805-814, 2010	57	2010
Predicting Continuous Conflict Perception with Bayesian Gaussian Processes S Kim, F Valente, M Filippone, A Vinciarelli IEEE Transactions on Affective Computing 5 (2), 187-200, 2014	54	2014
Automated, high accuracy classification of parkinsonian disorders: a pattern recognition approach AF Marquand, M Filippone, J Ashburner, M Girolami, J Mourao-Miranda, ... PloS one 8 (7), e69237, 2013	50	2013
Calibrating deep convolutional gaussian processes GL Tran, EV Bonilla, J Cunningham, P Michiardi, M Filippone The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	49	2019

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