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- W3035630265 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." @default.
- W3035630265 created "2020-06-19" @default.
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- W3035630265 date "2020-07-01" @default.
- W3035630265 modified "2023-10-17" @default.
- W3035630265 title "Toward a neuro-inspired creative decoder" @default.
- W3035630265 doi "https://doi.org/10.24963/ijcai.2020/381" @default.
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