Maurizio Filippone
Maurizio Filippone
Associate Professor - Statistics Program, KAUST
Verified email at - Homepage
Cited by
Cited by
A survey of kernel and spectral methods for clustering
M Filippone, F Camastra, F Masulli, S Rovetta
Pattern recognition 41 (1), 176-190, 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
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
MCMC for variationally sparse Gaussian processes
J Hensman, AG Matthews, M Filippone, Z Ghahramani
Advances in neural information processing systems 28, 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
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
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
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
Decoding post-stroke motor function from structural brain imaging
JM Rondina, M Filippone, M Girolami, NS Ward
NeuroImage: Clinical 12, 372-380, 2016
Preconditioning kernel matrices
K Cutajar, MA Osborne, JP Cunningham, M Filippone
Proceedings of the 33rd International Conference on Machine Learning, 2529-2538, 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
Pseudo-marginal Bayesian inference for Gaussian processes
M Filippone, M Girolami
IEEE Transactions on Pattern Analysis and Machine Intelligence 36 (11), 2214 …, 2014
A comparative evaluation of stochastic-based inference methods for Gaussian process models
M Filippone, M Zhong, M Girolami
Machine Learning 93, 93-114, 2013
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
AutoGP: Exploring the capabilities and limitations of Gaussian process models
K Krauth, EV Bonilla, K Cutajar, M Filippone
arXiv preprint arXiv:1610.05392, 2016
Deep compositional spatial models
A Zammit-Mangion, TLJ Ng, Q Vu, M Filippone
Journal of the American Statistical Association 117 (540), 1787-1808, 2022
Information theoretic novelty detection
M Filippone, G Sanguinetti
Pattern Recognition 43 (3), 805-814, 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
Probabilistic prediction of neurological disorders with a statistical assessment of neuroimaging data modalities
M Filippone, AF Marquand, CRV Blain, SCR Williams, J Mourão-Miranda, ...
The annals of applied statistics 6 (4), 1883, 2012
Population MCMC methods for history matching and uncertainty quantification
L Mohamed, B Calderhead, M Filippone, M Christie, M Girolami
Computational Geosciences 16, 423-436, 2012
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