I've been running into the idea of computational graphs a lot recently. It's at the core of Tensorflow (and NN in general) but it also comes up for example in Apple's AVFoundation where all audio processing happens in a graph of audio units. Does anyone know what's the theoretical foundation of computational graphs? EDIT: I've created a wiki page for computational graphs. https://en.wikipedia.org/wiki/Computational_G…
There is the biological analogue, which has inspired neural networks: > Recall that in our general definition a feed-forward neural network is a computational graph whose nodes are computing units and whose directed edges transmit numerical information from node to node. > Each computing unit is capable of evaluating a single primitive function of its input. In fact the network represents a chain of function composit…
I'm somewhat aware but it seems like the idea of a computational graph is the most generic computational idea I can think of and I'm surprised it's not more explored.
> Another ancestor would be the Data-Flow paradigm:
Oh yeah, data flow is definitely another one.