Facilitating neural networks

Abstract

Techniques for improved neural network modeling are provided. In one embodiment, a system comprises a memory that stores computer-executable components and a processor that executes the components. The computer-executable components can comprise a loss function logic component that determines a penalty based on a training term, the training term being a function of a relationship between an output scalar value of a first neuron of a plurality of neurons of a neural network model, a plurality of input values from the first neuron, and one or more tunable weights of connections between the plurality of neurons; an optimizer component that receives the penalty from the loss function component, and changes one or more of the tunable weights based on the penalty; and an output component that generates one or more output values indicating whether a defined pattern is detected in unprocessed input values received at the neural network evaluation component.