| Quantifying uncertainties on excursion sets under a Gaussian random field prior D Azzimonti, J Bect, C Chevalier, D Ginsbourger SIAM/ASA J. Uncertainty Quantification 4 (1), 850-874, 2016 | 42 | 2016 |
| Adaptive design of experiments for conservative estimation of excursion sets D Azzimonti, D Ginsbourger, C Chevalier, J Bect, Y Richet Technometrics 63 (1), 13-26, 2021 | 33 | 2021 |
| Reducing probes for quality of transmission estimation in optical networks with active learning D Azzimonti, C Rottondi, M Tornatore Journal of Optical Communications and Networking 12 (1), A38-A48, 2020 | 26 | 2020 |
| Optical properties of deposit models for paints: full-fields FFT computations and representative volume element DF Azzimonti, F Willot, D Jeulin Journal of Modern Optics 60 (7), 519-528, 2013 | 26 | 2013 |
| Active vs Transfer Learning Approaches for QoT Estimation with Small Training Datasets D Azzimonti, C Rottondi, A Giusti, M Tornatore, A Bianco Optical Fiber Communication Conference, M4E. 1, 2020 | 21 | 2020 |
| Estimating orthant probabilities of high dimensional Gaussian vectors with an application to set estimation D Azzimonti, D Ginsbourger Journal of Computational and Graphical Statistics 27 (2), 255-267, 2018 | 19 | 2018 |
| Recursive estimation for sparse Gaussian process regression M Schürch, D Azzimonti, A Benavoli, M Zaffalon Automatica 120, 109127, 2020 | 14 | 2020 |
| Using active learning to decrease probes for QoT estimation in optical networks D Azzimonti, C Rottondi, M Tornatore Optical Fiber Communication Conference, Th1H. 1, 2019 | 14 | 2019 |
| Comparison of domain adaptation and active learning techniques for quality of transmission estimation with small-sized training datasets D Azzimonti, C Rottondi, A Giusti, M Tornatore, A Bianco Journal of Optical Communications and Networking 13 (1), A56-A66, 2021 | 12 | 2021 |
| Profile Extrema for Visualizing and Quantifying Uncertainties on Excursion Regions: Application to Coastal Flooding D Azzimonti, D Ginsbourger, J Rohmer, D Idier Technometrics 61 (4), 474-493, 2019 | 10 | 2019 |
| Skew Gaussian processes for classification A Benavoli, D Azzimonti, D Piga Machine Learning 109 (9), 1877-1902, 2020 | 9 | 2020 |
| KrigInv: Kriging-Based Inversion for Deterministic and Noisy Computer Experiments C Chevalier, V Picheny, D Ginsbourger, D Azzimonti R package version 1 (1), 2018 | 8 | 2018 |
| Contributions to Bayesian Set Estimation Relying on Random Field Priors DF Azzimonti Philosophisch-naturwissenschaftliche Fakultät der Universität Bern, 2016 | 8 | 2016 |
| Preferential Bayesian optimisation with skew gaussian processes A Benavoli, D Azzimonti, D Piga Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 7 | 2021 |
| A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes A Benavoli, D Azzimonti, D Piga Machine Learning 110 (11), 3095-3133, 2021 | 2 | 2021 |
| Reconciling Hierarchical Forecasts via Bayes' Rule G Corani, D Azzimonti, JPSC Augusto, M Zaffalon arXiv preprint arXiv:1906.03105, 2019 | 2 | 2019 |
| Conservative estimates of excursion sets in reliability engineering D Azzimonti, D Ginsbourger, C Chevalier, Y Richet 47èmes Journées de Statistique de la SFdS, 2015 | 2 | 2015 |
| Sparse Information Filter for Fast Gaussian Process Regression L Kania, M Schürch, D Azzimonti, A Benavoli ECML PKDD 2021: Machine Learning and Knowledge Discovery in Databases, 2021 | 1 | 2021 |
| Probabilistic reconciliation of hierarchical forecast via Bayes’ rule G Corani, D Azzimonti, JPSC Augusto, M Zaffalon Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020 | 1 | 2020 |
| Quantifying and reducing uncertainties on excursion sets under a gaussian random field prior D Ginsbourger, C Chevalier, J Bect, DF Azzimonti, I Molchanov 2nd Conference of the International Society of NonParametric Statistics (ISNPS), 2014 | 1 | 2014 |
David GinsbourgerUniversity of BernVerified email at stat.unibe.ch
