ELU

ELU uses a smooth exponential structure in the negative region instead of hard zeroing, which can help produce a more balanced distribution of activations. This may allow representations to behave closer to being zero-centered and can facilitate learning in some cases. Although slightly more expensive than ReLU computationally, it may offer more stable optimization in certain architectures.