As I understand, deeplearn.js is more of a kitchen than a prepared meal. Part of the library is referred to as “numpy for the web” with classes to run linear algebra equations efficiently, leveraging the GPU. I don’t see why you couldn’t use those pieces to set up other networks. I think the name “deeplearn.js” is moreso capitalizing on the branding momentum of “deep learning” rather than being the demonstration of one kind of network. I’m in the middle of introductory machine learning classes, so I hope someone will correct me if I’m wrong.
We wanted to do hardware accelerated deep learning on the web, but we realized there was no NumPy equivalence. Our linear algebra layer has now matured to a place where we can start building a more functional automatic differentiation layer. We're going to completely remove the Graph in favor of a much simpler API by end of January.
Once that happens, we'll continue to build higher level abstractions that folks are familiar with: layers, networks, etc.
We really started from nothing, but we're getting there :)
http://www.asimovinstitute.org/neural-network-zoo/