3 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.LG2019★ 3 cited
Transforming the output of GANs by fine-tuning them with features from different datasets
Terence Broad, Mick Grierson
In this work we present a method for fine-tuning pre-trained GANs with features from different datasets, resulting in the transformation of the output distribution into a new distr…
cs.LG2019★ 2 cited
Searching for an (un)stable equilibrium: experiments in training generative models without data
Terence Broad, Mick Grierson
This paper details a developing artistic practice around an ongoing series of works called (un)stable equilibrium. These works are the product of using modern machine toolkits to t…