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Increase the collective knowledge inside your company

At Euranova, our scientific approach gives us a clear view of the issues to be addressed in the fields of AI and data science. Through our research centre, we have a firm grasp of the scientific topics we deal with and the technologies we use in our research projects and with our clients.

To share this technological knowledge with our academic and business partners and our customers, we propose tailor-made practical or applied workshops. We challenge our trainees’ everyday experiences with emerging digital opportunities. Our experts share their leading-edge knowledge and experiences with your teams.

If you want to grow your technical teams’ skills and accelerate your adaptation to new digital developments, do not hesitate to look at our training offers.

Download our training catalogue here.

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Investigating a Feature Unlearning Bias Mitigation Technique for Cancer-type Bias in AutoPet Dataset

We proposed a feature unlearning technique to reduce cancer-type bias, which improved segmentation accuracy while promoting fairness across sub-groups, even with limited data.
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Muppet: A Modular and Constructive Decomposition for Perturbation-based Explanation Methods

The topic of explainable AI has recently received attention driven by a growing awareness of the need for transparent and accountable AI. In this paper, we propose a novel methodology to decompose any state-of-the-art perturbation-based explainability approach into four blocks. In addition, we provide Muppet: an open-source Python library for explainable AI.
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