{"ID":2827878,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.15116","arxiv_id":"2512.15116","title":"FADTI: Fourier and Attention Driven Diffusion for Multivariate Time Series Imputation","abstract":"Multivariate time series imputation is fundamental in applications such as healthcare, traffic forecasting, and biological modeling, where sensor failures and irregular sampling lead to pervasive missing values. However, existing Transformer- and diffusion-based models lack explicit inductive biases and frequency awareness, limiting their generalization under structured missing patterns and distribution shifts. We propose FADTI, a diffusion-based framework that injects frequency-informed feature modulation via a learnable Fourier Bias Projection (FBP) module and combines it with temporal modeling through self-attention and gated convolution. FBP supports multiple spectral bases, enabling adaptive encoding of both stationary and non-stationary patterns. This design injects frequency-domain inductive bias into the generative imputation process. Experiments on multiple benchmarks, including a newly introduced biological time series dataset, show that FADTI consistently outperforms state-of-the-art methods, particularly under high missing rates. Code is available at https://anonymous.4open.science/r/TimeSeriesImputation-52BF","short_abstract":"Multivariate time series imputation is fundamental in applications such as healthcare, traffic forecasting, and biological modeling, where sensor failures and irregular sampling lead to pervasive missing values. However, existing Transformer- and diffusion-based models lack explicit inductive biases and frequency aware...","url_abs":"https://arxiv.org/abs/2512.15116","url_pdf":"https://arxiv.org/pdf/2512.15116v1","authors":"[\"Runze Li\",\"Hanchen Wang\",\"Wenjie Zhang\",\"Binghao Li\",\"Yu Zhang\",\"Xuemin Lin\",\"Ying Zhang\"]","published":"2025-12-17T06:16:31Z","proceeding":"cs.LG","tasks":"[\"cs.LG\",\"cs.AI\"]","methods":"[\"Diffusion Model\",\"Transformer\"]","project_urls":"[\"https://anonymous.4open.science/r/TimeSeriesImputation-52BF\"]","has_code":false}