This new algorithm replaces the traditional forward and backward passes of backpropagation with two forward passes: one using positive (i.e. real) data and another using negative data. Each layer in ...

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.

Backpropagation through ODE solutions is supported using the adjoint method for constant memory cost. For usage of ODE solvers in deep learning applications, see reference [1]. As the solvers are ...

This work involves research and analysis of the topic of learning algorithms of neural networks. This paper presents network learning that is performed by regenerating neural connections. This type of ...