{"url":"/method/cgmm","slug":"cgmm","name":"CGMM","full_name":"Contextual Graph Markov Model","full_name_withheld":false,"description_markdown":"Contextual Graph Markov Model (CGMM) is an approach combining ideas from generative models and neural networks for the processing of graph data. It founds on a constructive methodology to build a deep architecture comprising layers of probabilistic models that learn to encode the structured information in an incremental fashion. Context is diffused in an efficient and scalable way across the graph vertexes and edges. The resulting graph encoding is used in combination with discriminative models to address structure classification benchmarks.\r\n\r\nDescription and image from: [Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing](https://arxiv.org/pdf/1805.10636.pdf)","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":"https://arxiv.org/abs/1805.10636v2","title":"Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"Graphs","area_id":"graphs","collection":"Graph Models","url":"/methods/category/graph-models","pwc_aliases":[]}],"n_papers_tagged":3,"archive_num_papers":null,"papers_newest_first":[{"paper":null,"title":"Cancer-inspired Genomics Mapper Model for the Generation of Synthetic DNA Sequences with Desired Genomics Signatures","date":"2023-05-01","arxiv_id":"2305.01475","n_code_links":0,"syntology":null},{"paper":null,"title":"A new perspective on probabilistic image modeling","date":"2022-03-21","arxiv_id":"2203.11034","n_code_links":0,"syntology":null},{"paper":"/paper/contextual-graph-markov-model-a-deep-and","title":"Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing","date":"2018-05-27","arxiv_id":"1805.10636","n_code_links":1,"syntology":null}],"papers_shown":3,"tasks":[{"task":"/task/density-estimation","name":"Density Estimation","papers":1},{"task":"/task/classification","name":"General Classification","papers":1}],"tasks_shown":2,"n_tasks":2,"usage_by_year":[{"year":"2018","papers":1},{"year":"2022","papers":1},{"year":"2023","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/cgmm"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}