Research map / Label-efficient and robust learning / Test-time adaptation
DTWNet: a Dynamic Time Warping Network
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use DTWNet warping-path gradient instead of SoftDTW | barycenter computation · UCR train | avg-loss: 27.75 -> 24.79 | Helped |
| use DTWNet gradient instead of SoftDTW | barycenter computation · UCR test | avg-loss: 33.08 -> 31.99 | Helped |
| use DTWNet gradient instead of SSG | barycenter computation · UCR test | avg-rank: 2.31 -> 2.21 | No clear effect |
| use DTW kernel instead of convolution kernel | classifier on synthetic sequences · synthetic planted patterns | test accuracy: 100% vs below 100% | Helped |
| add shape regularizer alpha to streaming DTW (ablation) | SPRING DTW kernel · half-circle synthetic data | learned kernel shape | Helped |
Closest papers by meaning
- Perturbed Dynamic Time Warping: A Probabilistic Framework and Generalized Variants (ICLR 2026 · similarity 0.89)
- Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves (ICML 2025 · similarity 0.84)
- TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning (ICML 2025 · similarity 0.84)
- Fortifying Time Series: DTW-Certified Robust Anomaly Detection (NeurIPS 2025 · similarity 0.83)
- Causal Temporal Representation Learning with Nonstationary Sparse Transition (NeurIPS 2024 · similarity 0.80)
- Rethinking Time Encoding via Learnable Transformation Functions (ICML 2025 · similarity 0.80)
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