{"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/deep-learning-in-neural-networks-an-overview","title":"Deep Learning in Neural Networks: An Overview","arxiv_id":"1404.7828","date":"2014-04-30","proceeding":null,"authors":["Juergen Schmidhuber"],"abstract":"In recent years, deep artificial neural networks (including recurrent ones)\nhave won numerous contests in pattern recognition and machine learning. This\nhistorical survey compactly summarises relevant work, much of it from the\nprevious millennium. Shallow and deep learners are distinguished by the depth\nof their credit assignment paths, which are chains of possibly learnable,\ncausal links between actions and effects. I review deep supervised learning\n(also recapitulating the history of backpropagation), unsupervised learning,\nreinforcement learning & evolutionary computation, and indirect search for\nshort programs encoding deep and large networks.","url_abs":"http://arxiv.org/abs/1404.7828v4","url_pdf":"http://arxiv.org/pdf/1404.7828v4.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":"deep-learning-in-neural-networks-an-overview","repo_url":"https://github.com/pavitrakumar78/Playing-custom-games-using-Deep-Learning","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":"deep-learning","task_name":"Deep Learning"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1404.7828","atlas_url":"https://app.syntology.ai/?focus=1404.7828","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}