| Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources TW Lee, M Girolami, TJ Sejnowski Neural computation 11 (2), 417-441, 1999 | 2651 | 1999 |
| Riemann manifold langevin and hamiltonian monte carlo methods M Girolami, B Calderhead Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2011 | 2247 | 2011 |
| Mercer kernel-based clustering in feature space M Girolami IEEE transactions on neural networks 13 (3), 780-784, 2002 | 1221 | 2002 |
| Construction with digital twin information systems R Sacks, I Brilakis, E Pikas, HS Xie, M Girolami Data-centric engineering 1, e14, 2020 | 734 | 2020 |
| Hamiltonian Monte Carlo for hierarchical models M Betancourt, M Girolami Current trends in Bayesian methodology with applications 79 (30), 2-4, 2015 | 720 | 2015 |
| Blind source separation of more sources than mixtures using overcomplete representations TW Lee, MS Lewicki, M Girolami, TJ Sejnowski IEEE signal processing letters 6 (4), 87-90, 1999 | 645 | 1999 |
| Naturally occurring human urinary peptides for use in diagnosis of chronic kidney disease DM Good, P Zürbig, A Argiles, HW Bauer, G Behrens, JJ Coon, M Dakna, ... Molecular & cellular proteomics 9 (11), 2424-2437, 2010 | 613 | 2010 |
| A unifying information-theoretic framework for independent component analysis TW Lee, M Girolami, AJ Bell, TJ Sejnowski Computers & Mathematics with Applications 39 (11), 1-21, 2000 | 613 | 2000 |
| Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights A Malekloo, E Ozer, M AlHamaydeh, M Girolami Structural Health Monitoring 21 (4), 1906-1955, 2022 | 593 | 2022 |
| A first course in machine learning S Rogers, M Girolami Chapman and Hall/CRC, 2016 | 406 | 2016 |
| Building information modelling, artificial intelligence and construction tech R Sacks, M Girolami, I Brilakis Developments in the Built Environment 4, 100011, 2020 | 375 | 2020 |
| Clinical proteomics: a need to define the field and to begin to set adequate standards H Mischak, R Apweiler, RE Banks, M Conaway, J Coon, A Dominiczak, ... PROTEOMICS–Clinical Applications 1 (2), 148-156, 2007 | 368 | 2007 |
| Advances in urinary proteome analysis and biomarker discovery D Fliser, J Novak, V Thongboonkerd, V Jankowski, MA Girolami, ... Journal of the American Society of Nephrology 18 (4), 1057-1071, 2007 | 365 | 2007 |
| Recommendations for biomarker identification and qualification in clinical proteomics H Mischak, G Allmaier, R Apweiler, T Attwood, M Baumann, A Benigni, ... Science translational medicine 2 (46), 46ps42-46ps42, 2010 | 357 | 2010 |
| Probabilistic numerics and uncertainty in computations P Hennig, MA Osborne, M Girolami Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015 | 354 | 2015 |
| On an equivalence between PLSI and LDA M Girolami, A Kabán Proceedings of the 26th annual international ACM SIGIR conference on …, 2003 | 349 | 2003 |
| Kernel PCA for feature extraction and de-noising in nonlinear regression R Rosipal, M Girolami, LJ Trejo, A Cichocki Neural Computing & Applications 10 (3), 231-243, 2001 | 317 | 2001 |
| Bat detective—Deep learning tools for bat acoustic signal detection O Mac Aodha, R Gibb, KE Barlow, E Browning, M Firman, R Freeman, ... PLoS computational biology 14 (3), e1005995, 2018 | 311 | 2018 |
| Probability density estimation from optimally condensed data samples M Girolami, C He IEEE Transactions on pattern analysis and machine intelligence 25 (10), 1253 …, 2003 | 310 | 2003 |
| Variational Bayesian multinomial probit regression with Gaussian process priors M Girolami, S Rogers Neural Computation 18 (8), 1790-1817, 2006 | 306 | 2006 |
Chris. J. OatesNewcastle UniversityVerified email at ncl.ac.uk
