| Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting | Aug 5, 2022 | Time SeriesTime Series Analysis | CodeCode Available | 1 | 5 |
| Dynamic Data Augmentation with Gating Networks for Time Series Recognition | Nov 5, 2021 | Data AugmentationTime Series | CodeCode Available | 1 | 5 |
| Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warping | Feb 10, 2021 | ClusteringDynamic Time Warping | CodeCode Available | 1 | 5 |
| Autoregressive Moving-average Attention Mechanism for Time Series Forecasting | Oct 4, 2024 | DecoderTime Series | CodeCode Available | 1 | 5 |
| Adversarial Vulnerabilities in Large Language Models for Time Series Forecasting | Dec 11, 2024 | Adversarial AttackTime Series | CodeCode Available | 1 | 5 |
| DTAAD: Dual Tcn-Attention Networks for Anomaly Detection in Multivariate Time Series Data | Feb 17, 2023 | Anomaly DetectionDiagnostic | CodeCode Available | 1 | 5 |
| MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learning | Jun 7, 2024 | Contrastive LearningLanguage Modeling | CodeCode Available | 1 | 5 |
| Do We Really Need Deep Learning Models for Time Series Forecasting? | Jan 6, 2021 | Deep Learningregression | CodeCode Available | 1 | 5 |
| Adversarial Sparse Transformer for Time Series Forecasting | Dec 1, 2020 | Multivariate Time Series ForecastingPrediction | CodeCode Available | 1 | 5 |
| D-PAD: Deep-Shallow Multi-Frequency Patterns Disentangling for Time Series Forecasting | Mar 26, 2024 | Time SeriesTime Series Forecasting | CodeCode Available | 1 | 5 |
