Computational Creativity and Deep Generative Design: bridging the gap
Over the last few years, various models that use deep learning for generation and creation have become increasingly popular, e.g., GANs, VAEs. These deep generative design models create new media across images, text and music. Computational creativity has explored and continues to explore how surprise, curiosity, novelty, and other evaluative criteria, can be formalised for use by creative software in the sciences, the arts, literature, gaming and elsewhere.
This one-day workshop explores issues in the application of evaluation metrics from computational creativity to these deep generative models. The intent is to explore both how deep generative models can be more effectively used in computational creativity, and how evaluation metrics from computational creativity might contribute to deep generative models more generally. By bringing together researchers from both fields the workshop will explore the potential to improve deep generative design.
Areas of interest
GANs, VAEs & variants · Incorporating computational creativity metrics · Increasing diversity in generated artefacts · Adding more autonomy to models · Computational creativity in latent spaces · Generating more targeted artefacts · Innovation engines
Attendees will be able to access all accepted abstracts before attending the workshop to aid in an open atmosphere of discussion.
Attendees will submit extended abstracts (~400wds, about one page) that they are willing to present and discuss.
Extended Abstracts: abstracts should cover radical ideas on how deep generative design can use concepts and ideas from computational creativity, e.g., various metrics of creativity. These abstracts can cover works-in-progress or new directions for deep generative design. Abstracts should be focussed on ideas that can generate discussion and ideation.
Workshop submission deadline: M̶a̶y̶ ̶5̶t̶h̶ May 11th, 2019
Acceptance Notification: M̶a̶y̶ ̶5̶t̶h̶ May 20th, 2019
Workshop dates: June 17-18, 2019
Jer Hayes, Accenture.
Mary Lou Maher, University of North Carolina at Charlotte.
Rob Saunders, University of Sydney.
Kazjon Grace, University of Sydney.
Antionios Liapis, University of Malta.
Daniele Gravina, University of Malta.
Ahmed Elgamma, Rutgers University.