Fabian Guignard
Cited by
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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
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
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
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
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
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
Uncertainty quantification in extreme learning machine: Analytical developments, variance estimates and confidence intervals
F Guignard, F Amato, M Kanevski
Neurocomputing 456, 436-449, 2021
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
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
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
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
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
On Spatio-Temporal Data Modelling and Uncertainty Quantification Using Machine Learning and Information Theory
F Guignard
Springer Nature, 2022
On Feature Selection Using Anisotropic General Regression Neural Network
F Amato, F Guignard, P Jacquet, M Kanevski
arXiv preprint arXiv:2010.05744, 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
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
Wind of change: predicting wind potentials for the energy transition
F Amato, F Guignard, A Walch
EGU General Assembly Conference Abstracts, EGU21-4581, 2021
Model Variance for Extreme Learning Machine.
F Guignard, M Laib, MF Kanevski
ESANN, 703-708, 2020
Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains
L Telesca, F Guignard, N Helbig, M Kanevski
Energies 12 (16), 3048, 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
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