A new computational study shows that a constrained Hebbian learning rule achieves lower representational cost than ...

As artificial intelligence becomes more powerful, its ability to handle humanlike tasks is undeniable. Artificial neural ...

Pretraining Transformers Without Backpropagation" is a proposal for a computational algorithm and training framework that ...

Researchers at the University of Tokyo show that a single recurrent spiking neural network can learn event identity, timing, ...

A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI. Every time a human or machine learns how ...

A backpropagation algorithm, or backward propagation of errors, is an algorithm that's used to help train neural network models. The algorithm adjusts the network's weights to minimize any gaps -- ...