11 citations · 32 across the 7 of their papers we have counts for
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cs.LG2021★ 7 cited
Active Divergence with Generative Deep Learning -- A Survey and Taxonomy
Terence Broad, Sebastian Berns, Simon Colton +1
Generative deep learning systems offer powerful tools for artefact generation, given their ability to model distributions of data and generate high-fidelity results. In the context…
cs.LG2021★ 4 cited
Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities
Sebastian Berns, Terence Broad, Christian Guckelsberger +1
We present a framework for automating generative deep learning with a specific focus on artistic applications. The framework provides opportunities to hand over creative responsibi…