Toward a neuro-inspired creative decoder

5Citations
Citations of this article
21Readers
Mendeley users who have this article in their library.

Abstract

Creativity, a process that generates novel and meaningful ideas, involves increased association between task-positive (control) and task-negative (default) networks in the human brain. Inspired by this seminal finding, in this study we propose a creative decoder within a deep generative framework, which involves direct modulation of the neuronal activation pattern after sampling from the learned latent space. The proposed approach is fully unsupervised and can be used off-the-shelf. Several novelty metrics and human evaluation were used to evaluate the creative capacity of the deep decoder. Our experiments on different image datasets (MNIST, FMNIST, MNIST+FMNIST, WikiArt and CelebA) reveal that atypical co-activation of highly activated and weakly activated neurons in a deep decoder promotes generation of novel and meaningful artifacts.

Cite

CITATION STYLE

APA

Das, P., Quanz, B., Chen, P. Y., Ahn, J. W., & Shah, D. (2020). Toward a neuro-inspired creative decoder. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 2021-January, pp. 2746–2753). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2020/381

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free