Year: 2023
Type: article
Abstract: Johnston and Fusi recently investigated the emergence of disentangled representations when a neural network was trained to perform multiple simultaneous tasks. Such experiments explore the benefits of flexible representations and add to a growing field of research investigating the representational geometry of artificial and biological neural networks.
Source: Trends in Cognitive Sciences
Authors: Jenelle Feather, SueYeon Chung
Institutions: Flatiron Institute, New York University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $6,830
OpenAlex ID: W4381851306