STEP: Scientific Time-Series Encoder Pretraining via Cross-Domain Distillation

STEP: Scientific Time-Series Encoder Pretraining via Cross-Domain Distillation explores A pretraining framework that distills knowledge from existing foundation models to create a unified encoder for scientific time series data, addressing sparsity and heterogeneity challenges.. Commercial viability score: 7/10 in Time Series Representation Learning.