{"url":"/method/lsuv-initialization","slug":"lsuv-initialization","name":"LSUV Initialization","full_name":"Layer-Sequential Unit-Variance Initialization","full_name_withheld":false,"description_markdown":"**Layer-Sequential Unit-Variance Initialization** (**LSUV**) is a simple method for weight initialization for deep net learning. The initialization strategy involves the following two step:\r\n\r\n1) First, pre-initialize weights of each [convolution](https://paperswithcode.com/method/convolution) or inner-product layer with\r\northonormal matrices. \r\n\r\n2) Second, proceed from the first to the final layer, normalizing the variance of the output of each layer to be equal to one.","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":"http://arxiv.org/abs/1511.06422v7","title":"All you need is a good init","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Initialization","url":"/methods/category/initialization","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":null,"papers_newest_first":[{"paper":"/paper/all-you-need-is-a-good-init","title":"All you need is a good init","date":"2015-11-19","arxiv_id":"1511.06422","n_code_links":11,"syntology":{"ran":0,"of":19,"unverified":19,"pointer_only":2}}],"papers_shown":1,"tasks":[{"task":"/task/all","name":"All","papers":1},{"task":"/task/image-classification","name":"Image Classification","papers":1}],"tasks_shown":2,"n_tasks":2,"usage_by_year":[{"year":"2015","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/lsuv-initialization"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}