4 papers · 1 filter
Correct then Forecast: Observer State-Space Models for Time Series Forecasting
Alexis-Raja Brachet, Guillaume Clavier--Frémond, Abdelhakim Ziani +2
Time series forecasting requires extrapolating the dynamics of an observed process beyond the last available measurement. Yet recurrent forecasting models typically treat observati…
Time Series Forecasting Through the Lens of Dynamics
Alexis-Raja Brachet, Pierre-Yves Richard, Céline Hudelot
While deep learning is facing an homogenization across modalities led by Transformers, they are still challenged by shallow linear models in the time series forecasting task. Our h…
Neurosymbolic Conformal Classification
Arthur Ledaguenel, Céline Hudelot, Mostepha Khouadjia
The last decades have seen a drastic improvement of Machine Learning (ML), mainly driven by Deep Learning (DL). However, despite the resounding successes of ML in many domains, the…
Bond Graphs for multi-physics informed Neural Networks for multi-variate time series
Alexis-Raja Brachet, Pierre-Yves Richard, Céline Hudelot
In the trend of hybrid Artificial Intelligence techniques, Physical-Informed Machine Learning has seen a growing interest. It operates mainly by imposing data, learning, or archite…