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Topic: subcortical nuclei

ePoster
1 ePoster

In Artificial Intelligence and Computer Science

ePoster · Machine Learning

Toward hierarchical compositionality with shallow hierarchical networks

Francisco López, Judith Massmann, Jochen Triesch · Bernstein Conference 2024

Unlike conventional deep neural networks, the human brain has a myriad of direct connections from subcortical nuclei to all cortical areas [1,2]. These enable fast information transfer and facilitate hierarchical compositionality but have not yet been explored in artificial systems [3]. In this work, we present the Shallow Hierarchical Artificial Neural Network (SHANN), a novel brain-inspired architecture with shallow connections from the input to all the hierarchical processing layers. Like conventional deep networks, SHANNs can achieve high levels of abstraction in more hierarchical layers.