{"url":"/method/smish","slug":"smish","name":"Smish","full_name":"Smish","full_name_withheld":false,"description_markdown":"Smish is an activation function defined as $f(x)=x\\cdot \\text{tanh}(\\ln(1+\\sigma(x)))$ where $\\sigma(x)$ denotes the sigmoid function. A parameterized version was also described in the form $f(x)=\\alpha x\\cdot \\text{tanh}(\\ln(1+\\sigma(\\beta x)))$.\r\n\r\nPaper: Smish: A Novel Activation Function for Deep Learning Methods\r\n\r\nSource: https://www.mdpi.com/2079-9292/11/4/540","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":null,"title":null,"url_on_a_paper_host":false},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Activation Functions","url":"/methods/category/activation-functions","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":1,"papers_newest_first":[{"paper":null,"title":"ErfReLU: Adaptive Activation Function for Deep Neural Network","date":"2023-06-02","arxiv_id":"2306.01822","n_code_links":0,"syntology":null}],"papers_shown":1,"tasks":[],"tasks_shown":0,"n_tasks":0,"usage_by_year":[{"year":"2023","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/smish"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}