{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11501172","patent":{"patent_number":"US-11501172","title":"Accurately identifying members of training data in variational autoencoders by reconstruction error","assignee":null,"inventors":[],"filing_date":"2018-12-13T00:00:00.000Z","publication_date":"2022-11-15T00:00:00.000Z","cpc_codes":["G06N","G06F","G06N","G06N","G06N"],"num_claims":15,"abstract":"A system is described that can include a machine learning model and at least one programmable processor communicatively coupled to the machine learning model. The machine learning model can receive data, generate a continuous probability distribution associated with the data, sample a latent variable from the continuous probability distribution to generate a plurality of samples, and generate reconstructed data from the plurality of samples. The at least one programmable processor can compute a reconstruction error by determining a distance between the reconstructed data and the data, and generate, based on the reconstruction error, an indication representing whether a specific record within the received data was used to train the machine learning model. Related apparatuses, methods, techniques, non-transitory computer programmable products, non-transitory machine-readable medium, articles, and other systems are also within the scope of this disclosure."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Accurately identifying members of training data in variational autoencoders by reconstruction error","description":"A system is described that can include a machine learning model and at least one programmable processor communicatively coupled to the machine learning model. The machine learning model can receive da","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11501172","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11501172","citation_suggestion":"Patentable. \"Accurately identifying members of training data in variational autoencoders by reconstruction error\" (US-11501172). https://patentable.app/patents/US-11501172","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11501172","json":"https://patentable.app/api/llm-context/US-11501172","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T06:32:24.298Z"}