This is a simple implementation of backpropagation using computational graphs. Computational Graphs are directed acyclic graphs that represent mathematical expressions and facilitate the efficient ...

Backpropagation and Gradient Checking is a classic Neural Network problem usedto solve the given computational graph. Given the computational graph first forwardpropagate and predict the class label.

A new algorithm efficiently solves the graph isomorphism problem, which has puzzled computer scientists for decades.

We show that signal flow graph theory provides a simple way to relate two popular algorithms used for adapting dynamic neural networks, real-time backpropagation and backpropagation-through-time.

Two computer scientists found — in the unlikeliest of places — just the idea they needed to make a big leap in graph theory.