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Our system explores an open-ended space of statistical\nmodels to discover a good explanation of a data set, and then produces a\ndetailed report with figures and natural-language text. Our approach treats\nunknown regression functions nonparametrically using Gaussian processes, which\nhas two important consequences. First, Gaussian processes can model functions\nin terms of high-level properties (e.g. smoothness, trends, periodicity,\nchangepoints). Taken together with the compositional structure of our language\nof models this allows us to automatically describe functions in simple terms.\nSecond, the use of flexible nonparametric models and a rich language for\ncomposing them in an open-ended manner also results in state-of-the-art\nextrapolation performance evaluated over 13 real time series data sets from\nvarious domains.","url_abs":"http://arxiv.org/abs/1402.4304v3","url_pdf":"http://arxiv.org/pdf/1402.4304v3.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":"automatic-construction-and-natural-language","repo_url":"https://github.com/jamesrobertlloyd/gpss-research","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"automatic-construction-and-natural-language","repo_url":"https://github.com/jamesrobertlloyd/gp-structure-search","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"automatic-construction-and-natural-language","repo_url":"https://github.com/sutoiku/autostat","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"gaussian-processes","task_name":"Gaussian Processes"},{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1402.4304","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1402.4304"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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