| UQLab user manual–Kriging (Gaussian process modelling) C Lataniotis, S Marelli, B Sudret Report UQLab-V0, 9-105, 2015 | 189 | 2015 |
| Extending classical surrogate modeling to high dimensions through supervised dimensionality reduction: a data-driven approach C Lataniotis, S Marelli, B Sudret International Journal for Uncertainty Quantification 10 (1), 2020 | 109* | 2020 |
| Parametric hierarchical kriging for multi-fidelity aero-servo-elastic simulators—Application to extreme loads on wind turbines I Abdallah, C Lataniotis, B Sudret Probabilistic Engineering Mechanics 55, 67-77, 2019 | 60 | 2019 |
| UQLab user manual–The Input module C Lataniotis, S Marelli, B Sudret Report UQLab-V0, 9-102, 2015 | 55 | 2015 |
| The Gaussian process modelling module in UQLab C Lataniotis, S Marelli, B Sudret arXiv preprint arXiv:1709.09382, 2017 | 39 | 2017 |
| Stochastic spectral embedding S Marelli, PR Wagner, C Lataniotis, B Sudret International Journal for Uncertainty Quantification 11 (2), 2021 | 31 | 2021 |
| UQLab user manual–Support vector machines for regression M Moustapha, C Lataniotis, S Marelli, B Sudret Rep UQLab-V1, 3-111, 2018 | 23 | 2018 |
| Data-driven uncertainty quantification for high-dimensional engineering problems C Lataniotis ETH Zurich, 2019 | 15 | 2019 |
| Sparse polynomial chaos expansions as a machine learning regression technique B Sudret, S Marelli, C Lataniotis International Symposium on Big Data and Predictive Computational Modeling, 2015 | 9 | 2015 |
| Uncertainty quantification in the cloud with UQCloud C Lataniotis, S Marelli, B Sudret 4th International Conference on Uncertainty Quantification in Computational …, 2021 | 7 | 2021 |
| UQLib user manual M Moustapha, C Lataniotis, P Wiederkehr, PR Wagner, D Wicaksono, ... Report UQLab-V1, 3-201, 2019 | 7 | 2019 |
| UQLab user manual–Support vector machines for classification M Moustapha, C Lataniotis, S Marelli, B Sudret ETH Zurich, 2018 | 6 | 2018 |
| Hierarchical Kriging for multi-fidelity aero-servo-elastic simulators-Application to extreme loads on wind turbines I Abdallah, C Lataniotis, B Sudret arXiv preprint arXiv:1709.07637, 2017 | 6 | 2017 |
| Uqlab user manual-the model module C Lataniotis, S Marelli, B Sudret Report UQLab-V0. 9-103, 2015 | 5 | 2015 |
| Uqlab 2.0 and uqcloud: open-source vs. cloud-based uncertainty quantification C Lataniotis, S Marelli, B Sudret SIAM Conference on Uncertainty Quantification (SIAM UQ 2022), 2022 | 3 | 2022 |
| Fusing simulation results from multifidelity aero-servo-elastic simulators-Application to extreme loads on wind turbine I Abdallah, B Sudret, C Lataniotis, JD Sørensen, A Natarajan 12th International Conference on Applications of Statistics and Probability …, 2015 | 3 | 2015 |
| 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 |
| UQLab & UQ [py] Lab-project updates and outlook A Hlobilová, C Lataniotis, S Marelli, B Sudret 5th International Conference on Uncertainty Quantification in Computational …, 2023 | 1 | 2023 |
| Combining machine learning and surrogate modeling for data-driven uncertainty propagation in high-dimension C Lataniotis, S Marelli, B Sudret 3rd International Conference on Uncertainty Quantification in Computational …, 2019 | 1 | 2019 |
| An adaptive algorithm based on spectral likelihood expansion for efficient Bayesian calibration PR Wagner, C Lataniotis, S Marelli, B Sudret 3rd International Conference on Uncertainty Quantification in Computational …, 2019 | 1 | 2019 |
Bruno SudretETH ZurichVerified email at ethz.ch
