| Data-driven polynomial chaos expansion for machine learning regression E Torre, S Marelli, P Embrechts, B Sudret Journal of Computational Physics 388, 601-623, 2019 | 153 | 2019 |
| A general framework for data-driven uncertainty quantification under complex input dependencies using vine copulas E Torre, S Marelli, P Embrechts, B Sudret Probabilistic Engineering Mechanics 55, 1-16, 2019 | 121 | 2019 |
| Statistical evaluation of synchronous spike patterns extracted by frequent item set mining E Torre, D Picado-Muiño, M Denker, C Borgelt, S Grün Frontiers in computational neuroscience 7, 132, 2013 | 73* | 2013 |
| Synchronous spike patterns in macaque motor cortex during an instructed-delay reach-to-grasp task E Torre, P Quaglio, M Denker, T Brochier, A Riehle, S Grün Journal of Neuroscience 36 (32), 8329-8340, 2016 | 55 | 2016 |
| ASSET: analysis of sequences of synchronous events in massively parallel spike trains E Torre, C Canova, M Denker, G Gerstein, M Helias, S Grün PLoS computational biology 12 (7), e1004939, 2016 | 40 | 2016 |
| Detection and evaluation of spatio-temporal spike patterns in massively parallel spike train data with spade P Quaglio, A Yegenoglu, E Torre, DM Endres, S Grün Frontiers in computational neuroscience 11, 41, 2017 | 35 | 2017 |
| Methods for identification of spike patterns in massively parallel spike trains P Quaglio, V Rostami, E Torre, S Grün Biological cybernetics 112, 57-80, 2018 | 30 | 2018 |
| 3d-SPADE: Significance evaluation of spatio-temporal patterns of various temporal extents A Stella, P Quaglio, E Torre, S Grün Biosystems 185, 104022, 2019 | 21 | 2019 |
| A copula-based method to build diffusion models with prescribed marginal and serial dependence E Bibbona, L Sacerdote, E Torre Methodology and computing in applied probability 18, 765-783, 2016 | 14 | 2016 |
| An incubating diseased-predator ecoepidemic model C Tannoia, E Torre, E Venturino Journal of biological physics 38, 705-720, 2012 | 13 | 2012 |
| UQLab user manual–Statistical inference E Torre, S Marelli, B Sudret Chair of Risk, Safety and Uncertainty Quantification, 4-114, 2021 | 12 | 2021 |
| Statistical evaluation of synchronous spike patterns extracted by frequent item set mining. Front Comput Neurosci. 2013; 7 (132) E Torre, D Picado-Muiño, M Denker, C Borgelt, S Grün | 4 | 2013 |
| Maximum-entropy and representative samples of neuronal activity: a dilemma PGLP Mana, V Rostami, E Torre, Y Roudi arXiv preprint arXiv:1805.09084, 2018 | 3* | 2018 |
| Surrogate modelling meets machine learning B Sudret, C Lataniotis, N Lüthen, S Marelli, E Torre 3rd International Conference on Uncertainty Quantification in Computational …, 2019 | 2 | 2019 |
| Maximum-entropy and representative samples of neuronal activity: a dilemma PGL Porta Mana, V Rostami, E Torre, Y Roudi bioRxiv, 329193, 2018 | 1 | 2018 |
| Statistical analysis of synchrony and synchrony propagation in massively parallel spike trains E Torre Dissertation, RWTH Aachen, 2016, 2016 | 1 | 2016 |
| Vine copulas for uncertainty quantification: why and how E Torre, S Marelli, P Embrechts, B Sudret Vine Copulas and their Applications. Workshop at the Technical University of …, 2019 | | 2019 |
| Representation and Inference of Complex dependencies through copulas in UQLab E Torre, S Marelli, B Sudret 3rd International Conference on Uncertainty Quantification in Computational …, 2019 | | 2019 |
| Data-driven regression and uncertainty quantification by polynomial chaos expansions and vine copulas E Torre, S Marelli, P Embrechts, B Sudret 23rd International Conference on Computational Statistics (COMPSTAT 2018), A0285, 2018 | | 2018 |
| Maximum-entropy and representative samples of neuronal activity: a dilemma V Rostami, E Torre, Y Roudi | | 2018 |
