4 papers
A Rate-Distortion Perspective on the Emergence of Number Sense in Unsupervised Generative Models
Leo D'Amato, Davide Nuzzi, Alberto Testolin +3
Number sense is a core cognitive ability supporting various adaptive behaviors and is foundational for mathematical learning. Here, we study its emergence in unsupervised generativ…
GENESIS: A Generative Model of Episodic-Semantic Interaction
Marco D'Alessandro, Leo D'Amato, Mikel Elkano +2
A central challenge in cognitive neuroscience is to explain how semantic and episodic memory, two major forms of declarative memory, typically associated with cortical and hippocam…
The geometry of efficient codes: how rate-distortion trade-offs distort the latent representations of generative models
Leo D'Amato, Gian Luca Lancia, Giovanni Pezzulo
Living organisms rely on internal models of the world to act adaptively. These models, because of resource limitations, cannot encode every detail and hence need to compress inform…
Neural representation in active inference: using generative models to interact with -- and understand -- the lived world
Giovanni Pezzulo, Leo D'Amato, Francesco Mannella +4
This paper considers neural representation through the lens of active inference, a normative framework for understanding brain function. It delves into how living organisms employ…