Methods › General › Adaptive Activation Functions › AGLU
Adaptive Generalised Linear Unit
AGLU
Introduced by Konstantinos Panagiotis Alexandridis et al. in Adaptive Parametric Activation
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The Adaptive Parametric activation (APA) is defined as: APA(z,λ,κ) = (λ exp(−κz) + 1) ^(1/(-λ)), where λ and κ are learnable parameters. This activation function is a generalisation of the Sigmoid and the Gumbel activation functions and it is expressive and versatile. For example, APA can be used inside the channel attention mechanism instead of the Sigmoid activation, or it can be used inside the intermediate layers using the Adaptive Generalised Linear Unit (AGLU): AGLU(z,λ,κ) = z APA(z,λ,κ).
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Adaptive Parametric Activation 11 Jul 2024 · 1 repository · arXiv:2407.08567
Tasks archive 2025-07-28
3 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Instance Segmentation | 1 |
| Long-tail Learning | 1 |
| imbalanced classification | 1 |
Usage over time archive 2025-07-28
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Categories archive 2025-07-28
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