| A novel framework for spatio-temporal prediction of environmental data using deep learning F Amato, F Guignard, S Robert, M Kanevski Scientific reports 10 (1), 22243, 2020 | 110* | 2020 |
| Analysis of air pollution time series using complexity-invariant distance and information measures F Amato, M Laib, F Guignard, M Kanevski Physica A: Statistical Mechanics and its Applications 547, 124391, 2020 | 19 | 2020 |
| Spatio-temporal modelling and uncertainty estimation of hourly global solar irradiance using Extreme Learning Machines A Walch, R Castello, N Mohajeri, F Guignard, M Kanevski, JL Scartezzini Energy Procedia 158, 6378-6383, 2019 | 18 | 2019 |
| Investigating the time dynamics of wind speed in complex terrains by using the Fisher–Shannon method F Guignard, M Lovallo, M Laib, J Golay, M Kanevski, N Helbig, L Telesca Physica A: Statistical Mechanics and its Applications 523, 611-621, 2019 | 16 | 2019 |
| Spatio-temporal estimation of wind speed and wind power using extreme learning machines: predictions, uncertainty and technical potential F Amato, F Guignard, A Walch, N Mohajeri, JL Scartezzini, M Kanevski Stochastic environmental research and risk assessment 36 (8), 2049-2069, 2022 | 11 | 2022 |
| Advanced analysis of temporal data using Fisher-Shannon information: theoretical development and application in geosciences F Guignard, M Laib, F Amato, M Kanevski Frontiers in Earth Science 8, 255, 2020 | 11 | 2020 |
| Uncertainty quantification in extreme learning machine: Analytical developments, variance estimates and confidence intervals F Guignard, F Amato, M Kanevski Neurocomputing 456, 436-449, 2021 | 10 | 2021 |
| Fisher–Shannon Complexity Analysis of High-Frequency Urban Wind Speed Time Series F Guignard, D Mauree, M Lovallo, M Kanevski, L Telesca Entropy 21 (1), 47, 2019 | 10 | 2019 |
| Analysis of temporal properties of extremes of wind measurements from 132 stations over Switzerland L Telesca, F Guignard, M Laib, M Kanevski Renewable Energy 145, 1091-1103, 2020 | 8 | 2020 |
| Differences in click and speech auditory brainstem responses and cortical response patterns: A pilot study JF Knebel, A Jeanvoine, F Guignard, JM Vesin, C Richard Journal of Neurology and Neurophysiology 9, 463, 2018 | 7 | 2018 |
| Community detection analysis in wind speed-monitoring systems using mutual information-based complex network M Laib, F Guignard, M Kanevski, L Telesca Chaos: An Interdisciplinary Journal of Nonlinear Science 29 (4), 2019 | 5 | 2019 |
| Spatio-temporal evolution of global surface temperature distributions F Amato, F Guignard, V Humphrey, M Kanevski Proceedings of the 10th International Conference on Climate Informatics, 37-43, 2020 | 3 | 2020 |
| Linearity versus non-linearity in high frequency multilevel wind time series measured in urban areas L Telesca, M Laib, F Guignard, D Mauree, M Kanevski Chaos, Solitons & Fractals 120, 234-244, 2019 | 3 | 2019 |
| On Spatio-Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory F Guignard Springer Nature, 2022 | 2 | 2022 |
| On Feature Selection Using Anisotropic General Regression Neural Network F Amato, F Guignard, P Jacquet, M Kanevski arXiv preprint arXiv:2010.05744, 2020 | 2 | 2020 |
| Wavelet variance scale-dependence as a dynamics discriminating tool in high-frequency urban wind speed time series F Guignard, D Mauree, M Kanevski, L Telesca Physica A: Statistical Mechanics and its Applications 525, 771-777, 2019 | 2 | 2019 |
| Wind of change: predicting wind potentials for the energy transition F Amato, F Guignard, A Walch EGU General Assembly Conference Abstracts, EGU21-4581, 2021 | 1 | 2021 |
| Model Variance for Extreme Learning Machine. F Guignard, M Laib, MF Kanevski ESANN, 703-708, 2020 | 1 | 2020 |
| Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains L Telesca, F Guignard, N Helbig, M Kanevski Energies 12 (16), 3048, 2019 | 1 | 2019 |
| Feature selection using simple and efficient machine learning models. Case studies and software tools F Amato, F Guignard, M Kanevski Geophys. Res. Abstr 21, 4886, 2019 | 1 | 2019 |
Federico AmatoSenior Data Scientist, Swiss Data Science Center, École polytechnique fédérale de LausanneVerified email at epfl.ch
