CLaSP trains separate encoders for signals and text with a contrastive loss so that a natural language query can retrieve matching time-series signals without any predefined synonym dictionary.
A dynamic query interface for finding patterns in time series data,
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CLaSP: Learning Concepts for Time-Series Signals from Natural Language Supervision
CLaSP trains separate encoders for signals and text with a contrastive loss so that a natural language query can retrieve matching time-series signals without any predefined synonym dictionary.