Methods › General › Adaptive Activation Functions › DELU

DELU

2 papers tagged archive 2025-07-28

Introduced by Evgenii Pishchik in Trainable Activations for Image Classification

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

The DELU is a type of activation function that has trainable parameters, uses the complex linear and exponential functions in the positive dimension and uses the SiLU in the negative dimension.

DELU(x) = SiLU(x), x ⩽0 DELU(x) = (n + 0.5)x + |e⁻ˣ - 1|, x > 0

PaperSource

Papers archive 2025-07-28

2 shown of 2, 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.

Tasks archive 2025-07-28

2 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Image Classification1
image-classification1

Usage over time archive 2025-07-28

Papers per year tagged with DELU: 2023 to 2023, peak 2 2 0 2023: 2 papers 2023
Papers per year the archive tags with this method, by the paper's archive date (2 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Adaptive Activation FunctionsActivation Functions

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