| Advanced line sampling for efficient robust reliability analysis M de Angelis, E Patelli, M Beer Structural safety 52, 170-182, 2015 | 250 | 2015 |
| Reliability-based optimal design of nonlinear viscous dampers for the seismic protection of structural systems D Altieri, E Tubaldi, M De Angelis, E Patelli, A Dall’Asta Bulletin of Earthquake Engineering 16, 963-982, 2018 | 91 | 2018 |
| Uncertainty management in multidisciplinary design of critical safety systems E Patelli, DA Alvarez, M Broggi, M de Angelis Journal of Aerospace Information Systems 12 (1), 140-169, 2015 | 76 | 2015 |
| OpenCossan: An efficient open tool for dealing with epistemic and aleatory uncertainties E Patelli, M Broggi, M Angelis, M Beer Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and …, 2014 | 76 | 2014 |
| From inference to design: A comprehensive framework for uncertainty quantification in engineering with limited information A Gray, A Wimbush, M de Angelis, PO Hristov, D Calleja, E Miralles-Dolz, ... Mechanical Systems and Signal Processing 165, 108210, 2022 | 47 | 2022 |
| OpenCossan 2.0: an efficient computational toolbox for risk, reliability and resilience analysis E Patelli, S Tolo, H George-Williams, J Sadeghi, R Rocchetta, ... | 41 | 2018 |
| Development of a digital twin operational platform using Python Flask MS Bonney, M de Angelis, M Dal Borgo, L Andrade, S Beregi, N Jamia, ... Data-Centric Engineering 3, 2022 | 35 | 2022 |
| "No test is better than a bad test": Impact of diagnostic uncertainty in mass testing on the spread of Covid-19 N Gray, D Calleja, A Wimbush, E Miralles-Dolz, A Gray, M De Angelis, ... medRxiv, 2020 | 35 | 2020 |
| Robust propagation of probability boxes by interval predictor models J Sadeghi, M de Angelis, E Patelli Structural Safety 82, 101889, 2020 | 33 | 2020 |
| Efficient training of interval Neural Networks for imprecise training data J Sadeghi, M De Angelis, E Patelli Neural Networks 118, 338-351, 2019 | 29 | 2019 |
| On the Robust Estimation of Small Failure Probabilities for Strong Nonlinear Models M Faes, J Sadeghi, M Broggi, M De Angelis, E Patelli, M Beer, D Moens ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg 5 (4), 2019 | 28 | 2019 |
| Why the 1-Wasserstein distance is the area between the two marginal CDFs M De Angelis, A Gray arXiv preprint arXiv:2111.03570, 2021 | 20 | 2021 |
| Low-cost battery monitoring by converter-based electrochemical impedance spectroscopy R Ferrero, C Wu, A Carboni, S Toscani, M De Angelis, H George-Williams, ... 2017 IEEE International Workshop on Applied Measurements for Power Systems …, 2017 | 19 | 2017 |
| An integrated and efficient numerical framework for uncertainty quantification: application to the nasa langley multidisciplinary uncertainty quantification challenge E Patelli, DA Alvarez, M Broggi, M de Angelis 16th AIAA Non-Deterministic Approaches Conference, 1501, 2014 | 19 | 2014 |
| Forced Monte Carlo simulation strategy for the design of maintenance plans with multiple inspections M de Angelis, E Patelli, M Beer ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A …, 2017 | 17 | 2017 |
| Frequentist history matching with Interval Predictor Models J Sadeghi, M de Angelis, E Patelli Applied Mathematical Modelling 61, 29-48, 2018 | 16 | 2018 |
| Projecting interval uncertainty through the discrete Fourier transform: An application to time signals with poor precision M Behrendt, M de Angelis, L Comerford, Y Zhang, M Beer Mechanical Systems and Signal Processing 172, 108920, 2022 | 15 | 2022 |
| Digital Twin Operational Platform for Connectivity and Accessibility using Flask Python MS Bonney, M de Angelis, D Wagg, M Dal Borgo 2021 ACM/IEEE International Conference on Model Driven Engineering Languages …, 2021 | 15 | 2021 |
| Pseudo credal networks for inference with probability intervals HDE Lugo, S Tolo, M De Angelis, E Patelli ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2019 | 13* | 2019 |
| Contextualisation of information in digital twin processes MS Bonney, M de Angelis, M Dal Borgo, DJ Wagg Mechanical Systems and Signal Processing 184, 109657, 2023 | 12 | 2023 |
Edoardo PatelliUniversity of Strathclyde, Glasgow, UKZweryfikowany adres z strath.ac.uk