{"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/u-mixer-an-unet-mixer-architecture-with","title":"U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting","arxiv_id":"2401.02236","date":"2024-01-04","proceeding":null,"authors":["Xiang Ma","Xuemei Li","Lexin Fang","Tianlong Zhao","Caiming Zhang"],"abstract":"Time series forecasting is a crucial task in various domains. Caused by factors such as trends, seasonality, or irregular fluctuations, time series often exhibits non-stationary. It obstructs stable feature propagation through deep layers, disrupts feature distributions, and complicates learning data distribution changes. As a result, many existing models struggle to capture the underlying patterns, leading to degraded forecasting performance. In this study, we tackle the challenge of non-stationarity in time series forecasting with our proposed framework called U-Mixer. By combining Unet and Mixer, U-Mixer effectively captures local temporal dependencies between different patches and channels separately to avoid the influence of distribution variations among channels, and merge low- and high-levels features to obtain comprehensive data representations. The key contribution is a novel stationarity correction method, explicitly restoring data distribution by constraining the difference in stationarity between the data before and after model processing to restore the non-stationarity information, while ensuring the temporal dependencies are preserved. Through extensive experiments on various real-world time series datasets, U-Mixer demonstrates its effectiveness and robustness, and achieves 14.5\\% and 7.7\\% improvements over state-of-the-art (SOTA) methods.","url_abs":"https://arxiv.org/abs/2401.02236v1","url_pdf":"https://arxiv.org/pdf/2401.02236v1.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":"u-mixer-an-unet-mixer-architecture-with","repo_url":"https://github.com/XiangMa-Shaun/U-Mixer","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series-forecasting","task_name":"Time Series Forecasting"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2401.02236","atlas_url":"https://app.syntology.ai/?focus=2401.02236","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.02236"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/XiangMa-Shaun/U-Mixer","reach":null}],"summary":{"ran":4,"ran_draft_wrong":1,"unverified":1},"by_repo_kind":{"listed":{"samples":6,"ran":5,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":6,"samples":[{"code_sha256_prefix":"bb074f981fdd7960","entry":"Flatten_Head","repo":"XiangMa-Shaun/U-Mixer","repo_kind":"listed","path":"models/UMixer.py","file_url":"https://github.com/XiangMa-Shaun/U-Mixer/blob/HEAD/models/UMixer.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"bb074f981fdd7960"}},{"code_sha256_prefix":"f0ce90b8fe6a4a31","entry":"PatchEmbedding","repo":"XiangMa-Shaun/U-Mixer","repo_kind":"listed","path":"models/UMixer.py","file_url":"https://github.com/XiangMa-Shaun/U-Mixer/blob/HEAD/models/UMixer.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"f0ce90b8fe6a4a31"}},{"code_sha256_prefix":"5298b071dcfd049d","entry":"S_Correction","repo":"XiangMa-Shaun/U-Mixer","repo_kind":"listed","path":"models/UMixer.py","file_url":"https://github.com/XiangMa-Shaun/U-Mixer/blob/HEAD/models/UMixer.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"5298b071dcfd049d"}},{"code_sha256_prefix":"672119f21abac06b","entry":"channelMix_CI_pat","repo":"XiangMa-Shaun/U-Mixer","repo_kind":"listed","path":"models/UMixer.py","file_url":"https://github.com/XiangMa-Shaun/U-Mixer/blob/HEAD/models/UMixer.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"672119f21abac06b"}},{"code_sha256_prefix":"864710bbbf25d286","entry":"tempolMix_CI_pat","repo":"XiangMa-Shaun/U-Mixer","repo_kind":"listed","path":"models/UMixer.py","file_url":"https://github.com/XiangMa-Shaun/U-Mixer/blob/HEAD/models/UMixer.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"864710bbbf25d286"}},{"code_sha256_prefix":"489f557d2f7d6b62","entry":"Model","repo":"XiangMa-Shaun/U-Mixer","repo_kind":"listed","path":"models/UMixer.py","file_url":"https://github.com/XiangMa-Shaun/U-Mixer/blob/HEAD/models/UMixer.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"489f557d2f7d6b62"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}