  The Yin-Yang dataset was developed for research on biologically plausible
error backpropagation and deep learning in spiking neural networks. It serves
as an alternative to classic deep learning datasets, especially in algorithm-
and model-prototyping scenarios, by providing several advantages. First, it is
smaller and therefore faster to learn, thereby being better suited for the
deployment on neuromorphic chips with limited network sizes. Second, it
exhibits a very clear gap between the accuracies achievable using shallow as
compared to deep neural networks.
