Hi Robert,

Here's a clear and professional comparison of ReLU vs. LeakyReLU, with practical guidance on when to use each.

1.Use ReLU when:

• You want a simple, fast activation and training is stable.

• Your model is not suffering from "dead neurons" (i.e., too many activations stuck at zero).

2.Use LeakyReLU when:

• You observe that many neurons in your network are dying (inactive), especially in deeper networks.

• You need better gradient flow for negative inputs.

We're working with generative models (e.g., GANs), where LeakyReLU often improves convergence stability.