Research map / Time series / Foundation models for time series
Graphical Time Warping for Joint Alignment of Multiple Curves
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| joint alignment of pairs with graph-structured smoothness (GTW) instead of independent DTW per pair | multi-pair curve alignment · Synthetic 100 pairs, 10x10 grid | normalized alignment error | Helped |
| GTW vs DTW under increasing noise | multi-pair curve alignment · Synthetic 100 pairs, 10x10 grid | change in normalized error with noise | Helped |
| infinite-capacity reverse edges in dual graph (vs none or equal-weight reverse edge) (ablation) | GTW dual graph construction · Synthetic 100 pairs, 10x10 grid | validity of warping paths (DTW monotonicity/continuity) | Helped |
| GTW vs DTW for delay pattern estimation on astrocyte calcium movie (reference curve) | astrocyte calcium imaging · Astrocyte calcium movie | cleanliness of delay pattern (qualitative) | Helped |
Closest papers by meaning
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- Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves (ICML 2025 · similarity 0.86)
- TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning (ICML 2025 · similarity 0.85)
- Multimodal Disease Progression Modeling via Spatiotemporal Disentanglement and Multiscale Alignment (NeurIPS 2025 · similarity 0.81)
- Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data (AAAI 2024 · similarity 0.81)
- FastJAM: a Fast Joint Alignment Model for Images (NeurIPS 2025 · similarity 0.81)
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