{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/understanding-neural-networks-via-feature","title":"Understanding Neural Networks via Feature Visualization: A survey","arxiv_id":"1904.08939","date":"2019-04-18","proceeding":null,"authors":["Anh Nguyen","Jason Yosinski","Jeff Clune"],"abstract":"A neuroscience method to understanding the brain is to find and study the\npreferred stimuli that highly activate an individual cell or groups of cells.\nRecent advances in machine learning enable a family of methods to synthesize\npreferred stimuli that cause a neuron in an artificial or biological brain to\nfire strongly. Those methods are known as Activation Maximization (AM) or\nFeature Visualization via Optimization. In this chapter, we (1) review existing\nAM techniques in the literature; (2) discuss a probabilistic interpretation for\nAM; and (3) review the applications of AM in debugging and explaining networks.","url_abs":"http://arxiv.org/abs/1904.08939v1","url_pdf":"http://arxiv.org/pdf/1904.08939v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"understanding-neural-networks-via-feature","repo_url":"https://github.com/yoshihisa-furusawa/Activation_Maximization","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"survey","task_name":"Survey"}],"methods":[{"method_slug":"am","method_name":"AM"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1904.08939","atlas_url":"https://app.syntology.ai/?focus=1904.08939","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}