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A computational neuroscience encoding-decoding approach for explaining and comparing artificial and biological networks

CORDIS · observation · Publication date unknown

A computational neuroscience encoding-decoding approach for explaining and comparing artificial and biological networks Recent progress in artificial intelligence (AI) has been mostly due to machine learning and, in particular, deep artificial neural networks (ANNs). Deep learning has an increasing presence in everyday life, including critical applications such as medical diagnosis, transportation, and energy distribution. In response to this, the field of Explainable AI (XAI) has generated much effort in terms of techniques and algorithms to address this problem. However, there is still no consensus on a suite of technology to address these challenges, progress has been extremely limited, and the formal properties of such systems are under-studied. On the other hand, computational neuroscience (CNS) aims to discover the principles behind biological neural networks that enable the brain to support cognition, perception, and action. This project will employ the latest approaches and techniques used in the field of CNS to de

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recordType

award

status

SIGNED

region

EU

value

209914.56

unit

EUR