Paper: arxiv.org/abs/1809.02232
The conceptual expansion algorithm is able to extrapolate beyond the training data, hypothesizing the existence of models that aren’t directly supported by the training data
We think conceptual expansion may be potentially important for ML generalization and domain transfer too.
(Might be the first few-shot GAN?)