{"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/dynamicgem-a-library-for-dynamic-graph","title":"DynamicGEM: A Library for Dynamic Graph Embedding Methods","arxiv_id":"1811.10734","date":"2018-11-26","proceeding":null,"authors":["Palash Goyal","Sujit Rokka Chhetri","Ninareh Mehrabi","Emilio Ferrara","Arquimedes Canedo"],"abstract":"DynamicGEM is an open-source Python library for learning node representations\nof dynamic graphs. It consists of state-of-the-art algorithms for defining\nembeddings of nodes whose connections evolve over time. The library also\ncontains the evaluation framework for four downstream tasks on the network:\ngraph reconstruction, static and temporal link prediction, node classification,\nand temporal visualization. We have implemented various metrics to evaluate the\nstate-of-the-art methods, and examples of evolving networks from various\ndomains. We have easy-to-use functions to call and evaluate the methods and\nhave extensive usage documentation. Furthermore, DynamicGEM provides a template\nto add new algorithms with ease to facilitate further research on the topic.","url_abs":"http://arxiv.org/abs/1811.10734v1","url_pdf":"http://arxiv.org/pdf/1811.10734v1.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":"dynamicgem-a-library-for-dynamic-graph","repo_url":"https://github.com/palash1992/DynamicGEM","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"dynamic-graph-embedding","task_name":"Dynamic graph embedding"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"graph-embedding","task_name":"Graph Embedding"},{"task_slug":"graph-reconstruction","task_name":"Graph Reconstruction"},{"task_slug":"link-prediction","task_name":"Link Prediction"},{"task_slug":"node-classification","task_name":"Node Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}