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time-series-imputation

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lixus7 / Time-Series-Works-Conferences

Star 947

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

deep-learning time-series location spatio-temporal demand-forecasting probabilistic-models spatio-temporal-data anomaly-detection traffic-prediction spatio-temporal-modeling accident-detection multivariate-timeseries time-series-prediction spatio-temporal-prediction time-series-forecasting paper-list time-series-imputation travel-time-prediction
  • Updated Mar 10, 2026

The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.08516

machine-learning deep-learning time-series interpolation pytorch transformer imputation attention attention-mechanism irregular-sampling incomplete-data imputation-model missing-values self-attention impute time-series-imputation partially-observed-data partially-observed partially-observed-time-series incomplete-time-series
  • Updated Oct 1, 2025
  • Python

WenjieDu / Awesome_Imputation

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Star 410

Awesome Deep Learning for Time-Series Imputation, including an unmissable paper and tool list about applying neural networks to impute incomplete time series containing NaN missing values/data

benchmark machine-learning data-mining deep-learning time-series neural-network interpolation survey imputation missing-data missingness nan missing-values probablistic irregular-time-series time-series-imputation incomplete-time-series
  • Updated Mar 5, 2026
  • Python

ZLiu21 / awesome-tsfms-from-pre-training-to-post-training

Star 32

This repository collects awesome representative papers and resources for "From Pre-training to Post-training: A Survey on Time Series Foundation Models" (TechRxiv-26).

reinforcement-learning time-series time-series-classification fine-tuning post-training time-series-forecasting pre-training pre-trained-model time-series-anomaly-detection time-series-imputation foundation-models time-series-datasets
  • Updated Feb 1, 2026

gkoulis / paper-with-code-SIMPAT-2025

Star 2

Real-time imputation of missing environmental sensor data for fault-tolerant edge computing.

real-time time-series simulation paper internet-of-things C2EF edge dataset imputation missing-data naive edge-computing exponential-smoothing holt-winters triple-exponential-smoothing simple-exponential-smoothing time-series-forecasting missing-data-imputation environmental-data time-series-imputation seasonal-naive
  • Updated Oct 10, 2025
  • Python

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