Research map / Time series / Causal and generative time series
Multivariate Time Series Imputation with Generative Adversarial Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| GAN-based imputation with GRUI | time series imputation vs MF · KDD air quality 50% missing | MSE: 0.772 -> 0.743 | Helped |
| GAN-based imputation with GRUI | time series imputation vs mean filling · KDD air quality 90% missing | MSE: 1.002 -> 1.018 | Hurt |
| impute with GAN before RNN classifier | mortality prediction · PhysioNet | AUC: 0.848 -> 0.8603 | Helped |
| add time-decay GRUI cell instead of plain GRU (ablation) | GAN imputation · PhysioNet | AUC: 0.8029 -> 0.8603 | Helped |
| add time-decay GRUI cell instead of plain GRU (ablation) | GAN imputation · KDD air quality 50% missing | MSE: 0.794 -> 0.743 | Helped |
| add discriminative loss (lambda 0.15) to masked reconstruction loss (ablation) | GAN imputation · PhysioNet | AUC | Helped |
| increase discriminative loss weight lambda (ablation) | GAN imputation · KDD regression | MSE | Hurt |
Closest papers by meaning
- Generative Semi-supervised Learning for Multivariate Time Series Imputation (AAAI 2021 · similarity 0.94)
- Probabilistic Imputation for Time-series Classification with Missing Data (ICML 2023 · similarity 0.91)
- Frequency-aware Generative Models for Multivariate Time Series Imputation (NeurIPS 2024 · similarity 0.89)
- Missing Data Imputation by Reducing Mutual Information with Rectified Flows (NeurIPS 2025 · similarity 0.84)
- Diffusion Transformers for Imputation: Statistical Efficiency and Uncertainty Quantification (NeurIPS 2025 · similarity 0.84)
- Discretizing Continuous Time Series for Imputation with Masked Diffusion Training (NeurIPS 2026 · similarity 0.84)
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