Understanding how to use non-standard activation functions allows you to customize a neural network system. A neural network loosely models biological synapses and neurons. Neural network (NN) ...

Explore the role of activation functions in deep learning and how they help neural networks learn complex patterns.

Examples of activation functions are ReLU, sigmoid, or tanh functions and they can transform the weighted sum of inputs into an artificial neural network. Sound waves as a mediator for an ...

Examples of activation functions are ReLU, sigmoid, or tanh functions and they can transform the weighted sum of inputs into an artificial neural network.

Invariant natural killer T (iNKT) cells exist in a 'poised effector' state, which enables them to rapidly produce cytokines following activation. Using a nearly monospecific T cell receptor, they ...

We hypothesize that many behavioral functions of orexins (including regulation of sleep/wake cycling) reflect a fundamentally integrated function for orexins in translating motivational activation ...

Consider the multivariate nonparametric regression model. It is shown that estimators based on sparsely connected deep neural networks with ReLU activation function and properly chosen network ...

Making a smoothie, going for an evening walk, or having empathy for a loved one are all examples of executive functions that ...

Examples of activation functions are ReLU, sigmoid, or tanh functions and they can transform the weighted sum of inputs into an artificial neural network.