18 citations · 25 across the 7 of their papers we have counts for
4 papers · 1 filter
A New Approach for Explainable Multiple Organ Annotation with Few Data
Régis Pierrard, Jean-Philippe Poli, Céline Hudelot
Despite the recent successes of deep learning, such models are still far from some human abilities like learning from few examples, reasoning and explaining decisions. In this pape…
Sim-to-Real Domain Adaptation For High Energy Physics
Marouen Baalouch, Maxime Defurne, Jean-Philippe Poli +1
Particle physics or High Energy Physics (HEP) studies the elementary constituents of matter and their interactions with each other. Machine Learning (ML) has played an important ro…
Embedded Constrained Feature Construction for High-Energy Physics Data Classification
Noëlie Cherrier, Maxime Defurne, Jean-Philippe Poli +1
Before any publication, data analysis of high-energy physics experiments must be validated. This validation is granted only if a perfect understanding of the data and the analysis…
Consistent Feature Construction with Constrained Genetic Programming for Experimental Physics
Noëlie Cherrier, Jean-Philippe Poli, Maxime Defurne +1
A good feature representation is a determinant factor to achieve high performance for many machine learning algorithms in terms of classification. This is especially true for techn…