Multivariate Time Series Imputation

Benchmarks archive 2025-07-28

9 leaderboard tables shown for this task, 9 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

8 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

29 shown of 29 papers with code (38 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Neural Ordinary Differential Equations
  19 Jun 2018 56 repositories listed Syntology ran 89 of 124 samples · 35 unverified · 41 pointer-only (licence)
  Instead of specifying a discrete sequence of hidden layers, we parameterize the derivative of the hidden state using a neural network.
• Latent ODEs for Irregularly-Sampled Time Series
  8 Jul 2019 11 repositories listed Syntology ran 4 of 8 samples · 4 unverified · 3 pointer-only (licence)
  Time series with non-uniform intervals occur in many applications, and are difficult to model using standard recurrent neural networks (RNNs).
• GAIN: Missing Data Imputation using Generative Adversarial Nets
  7 Jun 2018 8 repositories listed Syntology ran 2 of 8 samples · 6 unverified · 1 pointer-only (licence)
  Accordingly, we call our method Generative Adversarial Imputation Nets (GAIN).
• Recurrent Neural Networks for Multivariate Time Series with Missing Values
  6 Jun 2016 7 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 2 pointer-only (licence)
  Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values.
• Deep Learning for Multivariate Time Series Imputation: A Survey
  6 Feb 2024 5 repositories listed
  This survey aims to serve as a valuable resource for researchers and practitioners in the field of time series analysis and missing data imputation tasks.
• PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series
  30 May 2023 5 repositories listed Syntology ran 0 of 21 samples · 21 unverified
  PyPOTS is an open-source Python library dedicated to data mining and analysis on multivariate partially-observed time series, i.
• ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs
  27 Feb 2019 5 repositories listed Syntology ran 2 of 7 samples · 5 unverified · 1 pointer-only (licence)
  ANODE has a memory footprint of O(L) + O(N_t), with the same computational cost as reversing ODE solve.
• BRITS: Bidirectional Recurrent Imputation for Time Series
  27 May 2018 5 repositories listed Syntology ran 2 of 4 samples · 2 unverified
  It is ubiquitous that time series contains many missing values.
• GP-VAE: Deep Probabilistic Time Series Imputation
  9 Jul 2019 4 repositories listed Syntology ran 0 of 12 samples · 12 unverified
  Multivariate time series with missing values are common in areas such as healthcare and finance, and have grown in number and complexity over the years.
• SAITS: Self-Attention-based Imputation for Time Series
  17 Feb 2022 3 repositories listed Syntology ran 3 of 10 samples · 7 unverified
  Missing data in time series is a pervasive problem that puts obstacles in the way of advanced analysis.
• Estimating Missing Data in Temporal Data Streams Using Multi-directional Recurrent Neural Networks
  23 Nov 2017 3 repositories listed
  Existing methods address this estimation problem by interpolating within data streams or imputing across data streams (both of which ignore important information) or ignoring the temporal aspect of the data and imposing…
• ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation
  4 Dec 2023 2 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  The exploitation of the inherent structures of spatiotemporal data enables our model to learn balanced signal-noise representations, making it generalizable for a variety of imputation problems.
• Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations
  26 May 2022 2 repositories listed
  In particular, we propose a novel class of attention-based architectures that, given a set of highly sparse discrete observations, learn a representation for points in time and space by exploiting a spatiotemporal…
• Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks
  31 Jul 2021 2 repositories listed Syntology ran 5 of 10 samples · 5 unverified · 9 pointer-only (licence)
  In particular, we introduce a novel graph neural network architecture, named GRIN, which aims at reconstructing missing data in the different channels of a multivariate time series by learning spatio-temporal…
• A user-driven case-based reasoning tool for infilling missing values in daily mean river flow records
  1 Aug 2006 2 repositories listed
  In this work, we introduce gapIt, a user-driven case-based reasoning tool for infilling gaps in daily mean river flow records.
• CoSTI: Consistency Models for (a faster) Spatio-Temporal Imputation
  31 Jan 2025 1 repository listed
  Multivariate Time Series Imputation (MTSI) is crucial for many applications, such as healthcare monitoring and traffic management, where incomplete data can compromise decision-making.
• SDA-GRIN for Adaptive Spatial-Temporal Multivariate Time Series Imputation
  4 Oct 2024 1 repository listed
  Existing imputation methods often ignore dynamic changes in spatial dependencies.
• Mining of Switching Sparse Networks for Missing Value Imputation in Multivariate Time Series
  16 Sep 2024 1 repository listed
  Here, we propose a missing value imputation method for multivariate time series, namely MissNet, that is designed to exploit temporal dependency with a state-space model and inter-correlation by switching sparse…
• Latent Space Score-based Diffusion Model for Probabilistic Multivariate Time Series Imputation
  13 Sep 2024 1 repository listed
  To address these issues, we propose the Latent Space Score-Based Diffusion Model (LSSDM) for probabilistic multivariate time series imputation.
• MTSCI: A Conditional Diffusion Model for Multivariate Time Series Consistent Imputation
  11 Aug 2024 1 repository listed
  A key research question is how to ensure imputation consistency, i.
• REGIONAL DATASETS FOR AIR QUALITY MONITORING IN EUROPEAN CITIES
  12 Jul 2024 1 repository listed
  The primary environmental health threat in the WHO European Region is air pollution, impacting the daily health and well-being of its citizens significantly.
• Higher-order Spatio-temporal Physics-incorporated Graph Neural Network for Multivariate Time Series Imputation
  16 May 2024 1 repository listed
  Also, graph-like optical flow, dynamic graphs, and missing impact can be obtained naturally by HSPGNN, which provides better dynamic analysis and explanation than traditional data-driven models.
• BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition
  28 Aug 2023 1 repository listed Syntology ran 5 of 6 samples · 1 unverified · 6 pointer-only (licence)
  More importantly, almost all methods assume the observations are sampled at regular time stamps, and fail to handle complex irregular sampled time series arising from different applications.
• Generative Semi-supervised Learning for Multivariate Time Series Imputation
  18 May 2021 1 repository listed
  In this paper, we propose a novel semi-supervised generative adversarial network model, named SSGAN, for missing value imputation in multivariate time series data.
• ORBITS: Online Recovery of Missing Blocks in Multiple Time Series Streams
  1 Nov 2020 1 repository listed
  In this paper, we introduce a new online recovery technique to recover multiple time series streams in linear time.
• Probabilistic sequential matrix factorization
  9 Oct 2019 1 repository listed
  In particular, we consider nonlinear Gaussian state-space models where sequential approximate inference results in the factorization of a data matrix into a dictionary and time-varying coefficients with potentially…
• NAOMI: Non-Autoregressive Multiresolution Sequence Imputation
  30 Jan 2019 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Missing value imputation is a fundamental problem in spatiotemporal modeling, from motion tracking to the dynamics of physical systems.
• imputeTS: Time Series Missing Value Imputation in R
  1 Jun 2017 1 repository listed
  The imputeTS package specializes on univariate time series imputation.
• Multiple imputation using chained equations: issues and guidance for practice
  30 Nov 2010 1 repository listed
  Multiple imputation by chained equations (MICE) is a flexible and practical approach to handling missing data.

Syntology lines on 13 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.