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cs.LG2023★ 1 cited
Towards Mode Balancing of Generative Models via Diversity Weights
Sebastian Berns, Simon Colton, Christian Guckelsberger
Large data-driven image models are extensively used to support creative and artistic work. Under the currently predominant distribution-fitting paradigm, a dataset is treated as gr…
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…