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

paper note, including personal comments, introduction, code etc - papernote/neural network/Calculus on Computational Graphs Backpropagation.md at master · xwzhong/papernote paper note, including ...

A puzzle that has long flummoxed computers and the scientists who program them has suddenly become far more manageable. A new algorithm efficiently solves the graph isomorphism problem, computer ...

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.

The Forward-Forward algorithm (FF) is comparable in speed to backpropagation but has the advantage that it can be used when the precise details of the forward computation are unknown.

We propose a class of neural models for graphs that do not rely on backpropagation for training, thus making learning more biologically plausible and amenable to parallel implementation in hardware.

They presented it in June at the ACM Symposium on Theory of Computing, where they detailed an exponentially better method for checking whether a graph is planar. “The new algorithm is a remarkable ...