Methods › General › Activation Functions › Smish

Smish

1 paper tagged archive 2025-07-28

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

Smish is an activation function defined as f(x)=x·tanh(ln(1+σ(x))) where σ(x) denotes the sigmoid function. A parameterized version was also described in the form f(x)=αx·tanh(ln(1+σ(βx))).

Paper: Smish: A Novel Activation Function for Deep Learning Methods

Source: https://www.mdpi.com/2079-9292/11/4/540

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.

ErfReLU: Adaptive Activation Function for Deep Neural Network
2 Jun 2023 · 0 repositories · arXiv:2306.01822

Tasks archive 2025-07-28

The archive attaches no task to a paper tagged with this method.

Usage over time archive 2025-07-28

Papers per year the archive tags with this method, by the paper's archive date (1 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

Activation Functions

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