{"url":"/method/pmish","slug":"pmish","name":"PMish","full_name":"Parametric Mish","full_name_withheld":false,"description_markdown":"The Parametric Mish, or PMish, is a modification of the Mish activation function that has a trainable parameter $\\beta$. This $\\beta$ parameter allows the network to dynamically adjust the smoothness of the activation function transition.\r\n\\begin{equation}\r\n    f(x) = x \\cdot \\tanh\\left(\\frac{\\ln(1 + e^{\\beta x})}{\\beta}\\right), \\beta > 0,\r\n\\end{equation}","description_state":"present","introduced_year":null,"introduced_by":{"title":"Enhancing GANs with MMD Neural Architecture Search, PMish Activation Function, and Adaptive Rank Decomposition","paper":"/paper/enhancing-gans-with-mmd-neural-architecture","first_author":"Prasanna Reddy Pulakurthi","n_authors":6,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/enhancing-gans-with-mmd-neural-architecture"},"source":{"url":"https://ieeexplore.ieee.org/document/10732016","title":"Enhancing GANs with MMD Neural Architecture Search, PMish Activation Function, and Adaptive Rank Decomposition","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/PrasannaPulakurthi/MMD-PMish-NAS/blob/main/archs/activation_functions.py","code_snippet_url_on_a_code_host":true,"categories":[{"area":"General","area_id":"general","collection":"Adaptive Activation Functions","url":"/methods/category/adaptive-activation-functions","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":1,"papers_newest_first":[{"paper":"/paper/enhancing-gans-with-mmd-neural-architecture","title":"Enhancing GANs with MMD Neural Architecture Search, PMish Activation Function, and Adaptive Rank Decomposition","date":"2024-10-23","arxiv_id":null,"n_code_links":1,"syntology":null}],"papers_shown":1,"tasks":[{"task":"/task/image-generation","name":"Image Generation","papers":1}],"tasks_shown":1,"n_tasks":1,"usage_by_year":[{"year":"2024","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/pmish"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}