5 papers · 1 filter
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…
Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning
Théo Moutakanni, Piotr Bojanowski, Guillaume Chassagnon +7
AI Foundation models are gaining traction in various applications, including medical fields like radiology. However, medical foundation models are often tested on limited tasks, le…
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…
A Complexity Map of Probabilistic Reasoning for Neurosymbolic Classification Techniques
Arthur Ledaguenel, Céline Hudelot, Mostepha Khouadjia
Neurosymbolic artificial intelligence is a growing field of research aiming to combine neural network learning capabilities with the reasoning abilities of symbolic systems. Inform…
Improving Neural-based Classification with Logical Background Knowledge
Arthur Ledaguenel, Céline Hudelot, Mostepha Khouadjia
Neurosymbolic AI is a growing field of research aiming to combine neural networks learning capabilities with the reasoning abilities of symbolic systems. This hybridization can tak…