Methods › General › Adaptive Activation Functions › PMish

Parametric Mish

PMish

1 paper tagged archive 2025-07-28

Introduced by Prasanna Reddy Pulakurthi et al. in Enhancing GANs with MMD Neural Architecture Search, PMish Activation Function, and Adaptive Rank Decomposition

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

The Parametric Mish, or PMish, is a modification of the Mish activation function that has a trainable parameter β. This β parameter allows the network to dynamically adjust the smoothness of the activation function transition. f(x) = x ·tanh((ln(1 + e^(βx)))/β), β> 0,

PaperSourceSee Code · PrasannaPulakurthi/MMD-PMish-NAS

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.

Tasks archive 2025-07-28

1 task 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 Generation1

Usage over time archive 2025-07-28

Papers per year tagged with PMish: 2024 to 2024, peak 1 1 0 2024: 1 paper 2024
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

Adaptive Activation Functions

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