Missing Values

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

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Most implemented papers archive 2025-07-28

30 shown of 264 papers with code (804 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.

• TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
  5 Jul 2022 7 repositories listed Syntology ran 1 of 4 samples · 3 unverified · 1 pointer-only (licence)
  We present TabPFN, a trained Transformer that can do supervised classification for small tabular datasets in less than a second, needs no hyperparameter tuning and is competitive with state-of-the-art classification…
• 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.
• Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees
  18 Sep 2023 5 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Through empirical evaluation across the benchmark, we demonstrate that our approach outperforms deep-learning generation methods in data generation tasks and remains competitive in data imputation.
• 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.
• CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
  7 Jul 2021 5 repositories listed Syntology ran 10 of 19 samples · 9 unverified · 1 pointer-only (licence)
  In this paper, we propose Conditional Score-based Diffusion models for Imputation (CSDI), a novel time series imputation method that utilizes score-based diffusion models conditioned on observed data.
• 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.
• Hybrid Recommender System based on Autoencoders
  24 Jun 2016 4 repositories listed
  A standard model for Recommender Systems is the Matrix Completion setting: given partially known matrix of ratings given by users (rows) to items (columns), infer the unknown ratings.
• Federated Causal Inference from Observational Data
  24 Aug 2023 3 repositories listed Syntology ran 4 of 6 samples · 2 unverified · 6 pointer-only (licence)
  In this article, we propose a framework to estimate causal effects from decentralized data sources.
• 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.
• Bayesian Temporal Factorization for Multidimensional Time Series Prediction
  14 Oct 2019 3 repositories listed
  In this paper, we propose a Bayesian temporal factorization (BTF) framework for modeling multidimensional time series -- in particular spatiotemporal data -- in the presence of missing values.
• On the consistency of supervised learning with missing values
  19 Feb 2019 3 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  A striking result is that the widely-used method of imputing with a constant, such as the mean prior to learning is consistent when missing values are not informative.
• Consumer-grade EEG-based Eye Tracking
  18 Mar 2025 2 repositories listed
  In addition to the dataset, code for data preprocessing and analysis is available to support reproducibility and further research.
• Stochastic gradient descent estimation of generalized matrix factorization models with application to single-cell RNA sequencing data
  29 Dec 2024 2 repositories listed
  Single-cell RNA sequencing allows the quantitation of gene expression at the individual cell level, enabling the study of cellular heterogeneity and gene expression dynamics.
• scVGAE: A Novel Approach using ZINB-Based Variational Graph Autoencoder for Single-Cell RNA-Seq Imputation
  13 Mar 2024 2 repositories listed
  Consequently, methods have been developed to model the data according to this distribution.
• TimEHR: Image-based Time Series Generation for Electronic Health Records
  9 Feb 2024 2 repositories listed
  Time series in Electronic Health Records (EHRs) present unique challenges for generative models, such as irregular sampling, missing values, and high dimensionality.
• ReMasker: Imputing Tabular Data with Masked Autoencoding
  25 Sep 2023 2 repositories listed
  We present ReMasker, a new method of imputing missing values in tabular data by extending the masked autoencoding framework.
• Forecasting Electric Vehicle Charging Station Occupancy: Smarter Mobility Data Challenge
  9 Jun 2023 2 repositories listed
  To fill that gap, the Smarter Mobility Data Challenge has focused on the development of forecasting models to predict EV charging station occupancy.
• 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…
• Unsupervised Anomaly Detection by Robust Collaborative Autoencoders
  1 Jan 2021 2 repositories listed
  Unsupervised anomaly detection plays a crucial role in many critical applications.
• not-MIWAE: Deep Generative Modelling with Missing not at Random Data
  23 Jun 2020 2 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  When a missing process depends on the missing values themselves, it needs to be explicitly modelled and taken into account while doing likelihood-based inference.
• Monash University, UEA, UCR Time Series Extrinsic Regression Archive
  19 Jun 2020 2 repositories listed
  We refer to this problem as Time Series Extrinsic Regression (TSER), where we are interested in a more general methodology of predicting a single continuous value, from univariate or multivariate time series.
• Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula
  18 Jun 2020 2 repositories listed
  The time required to fit the model scales linearly with the number of rows and the number of columns in the dataset.
• Selecting time-series hyperparameters with the artificial jackknife
  11 Feb 2020 2 repositories listed
  This article proposes a generalisation of the delete-d jackknife to solve hyperparameter selection problems for time series.
• Graph Markov Network for Traffic Forecasting with Missing Data
  10 Dec 2019 2 repositories listed
  Although missing values can be imputed, existing data imputation methods normally need long-term historical traffic state data.
• Deep learning for clustering of multivariate clinical patient trajectories with missing values
  15 Nov 2019 2 repositories listed
  Findings The problem of clustering multivariate short time series with many missing values is generally not well addressed in the literature.
• CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation
  23 May 2019 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified
  In order to jointly capture the self-attention across multiple dimensions, including time, location and the sensor measurements, while maintain low computational complexity, we propose a novel approach called…
• Generative Imputation and Stochastic Prediction
  22 May 2019 2 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  In order to make imputations, we train a simple and effective generator network to generate imputations that a discriminator network is tasked to distinguish.
• A Novel Bayesian Approach for Latent Variable Modeling from Mixed Data with Missing Values
  12 Jun 2018 2 repositories listed
  We consider the problem of learning parameters of latent variable models from mixed (continuous and ordinal) data with missing values.

Syntology lines on 14 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.