{"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/reproducibility-challenge-neurips-2019-report","title":"Reproducibility Challenge NeurIPS 2019 Report on \"Competitive Gradient Descent\"","arxiv_id":"2001.10820","date":"2020-01-26","proceeding":null,"authors":["Gopi Kishan"],"abstract":"This is a report for reproducibility challenge of NeurlIPS 2019 on the paper Competitive Gradient Descent (Schafer et al., 2019). The paper introduces a novel algorithm for the numerical computation of Nash equilibria of competitive two-player games. It avoids oscillatory and divergent behaviours seen in alternating gradient descent. The purpose of this report is to critically examine the reproducibility of the work by (Schafer et al., 2019), within the framework of the NeurIPS 2019 Reproducibility Challenge. The experiments replicated in this report confirms the results of the original study. Moreover, this project offers a Python (Pytorch based) implementation of the proposed CGD algorithm which can be found at the following public git repository: (https://github.com/GopiKishan14/Reproducibility_Challenge_NeurIPS_2019)","url_abs":"https://arxiv.org/abs/2001.10820v1","url_pdf":"https://arxiv.org/pdf/2001.10820v1.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":"reproducibility-challenge-neurips-2019-report","repo_url":"https://github.com/GopiKishan14/Reproducibility_Challenge_NeurIPS_2019","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2001.10820","atlas_url":"https://app.syntology.ai/?focus=2001.10820","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}