Equilibrium propagation defines an “energy” function in terms of the nodes of a neural network. Physically, this “total energy,” F, is a measure of the total pseudo-power of the network. It is the sum ...

Gradient descent looks at the network as a calculus function and adjusts the values to minimize the loss function. Next, we will look at a variety of neural network styles that learn from and also ...

Radial basis function networks were first conceived in the late 1980s when there were many unanswered questions about all types of neural networks, including standard single hidden layer neural ...

In the past year, what had been the world's largest neural net as measured by neural weights, OpenAI's GPT-3 natural language processing program, with 175 billion weights, was eclipsed by Google's ...