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The CHORAL project aims to enhance the predictive capabilities of neural networks by developing a statistical framework that bridges theoretical and practical aspects of learning from complex data. It focuses on improving representation learning through advanced mathematical models and algorithms, ultimately benefiting…
Rich internal representations of complex data are crucial to the predictive power of neural networks.
Unfortunately, current statistical analyses are restricted to over-simplified networks, whose representations (i.e., weight matrices) are either random, and/or project the data in comparatively very large or very low dimensional spaces; in many applications the situation is very different.
The modelisation of realistic data is another issue.
There is an urgent need to reconcile theory and practi…
ORGANISATION DES NATIONS UNIES POUR L'EDUCATION LA SCIENCE ET LA CULTURE - UNESCO
UNITED NATIONS EDUCATIONAL SCIENTIFIC AND CULTURAL ORGANIZATION
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