6 citations · 11 across the 6 of their papers we have counts for
6 papers
Astronomical Images Quality Assessment with Automated Machine Learning
Olivier Parisot, Pierrick Bruneau, Patrik Hitzelberger
Electronically Assisted Astronomy consists in capturing deep sky images with a digital camera coupled to a telescope to display views of celestial objects that would have been invi…
Forecasting Intraday Power Output by a Set of PV Systems using Recurrent Neural Networks and Physical Covariates
Pierrick Bruneau, David Fiorelli, Christian Braun +1
Accurate intraday forecasts of the power output by PhotoVoltaic (PV) systems are critical to improve the operation of energy distribution grids. We describe a neural autoregressive…
Landscape of High-performance Python to Develop Data Science and Machine Learning Applications
Oscar Castro, Pierrick Bruneau, Jean-Sébastien Sottet +1
Python has become the prime language for application development in the Data Science and Machine Learning domains. However, data scientists are not necessarily experienced programm…
Cold Start Active Learning Strategies in the Context of Imbalanced Classification
Etienne Brangbour, Pierrick Bruneau, Thomas Tamisier +1
We present novel active learning strategies dedicated to providing a solution to the cold start stage, i.e. initializing the classification of a large set of data with no attached…
Extracting localized information from a Twitter corpus for flood prevention
Etienne Brangbour, Pierrick Bruneau, Stéphane Marchand-Maillet +4
In this paper, we discuss the collection of a corpus associated to tropical storm Harvey, as well as its analysis from both spatial and topical perspectives. From the spatial persp…
Data-driven forecasting of solar irradiance
Pierrick Bruneau, Philippe Pinheiro, Yoann Didry
This paper describes a flexible approach to short term prediction of meteorological variables. In particular, we focus on the prediction of the solar irradiance one hour ahead, a t…