CORD: Learning Reusable Degradation Representations Across Heterogeneous Physical Systems
cs.LG
Submitted: 2026-09-30
Updated: 2026-09-30
Sources
- Chronos: Learning the Language of Time Series
- An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
- iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
- A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
- Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models
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