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cs.LG2026
Giving Sensors a Voice: Multimodal JEPA for Semantic Time-Series Embeddings
Utsav Dutta, Gerardo Pastrana, Sina Khoshfetrat Pakazad +1
Transformer-based architectures have advanced sequence modeling in language and vision, yet general-purpose representation learning for heterogeneous multivariate time series remai…
cs.LG2025
Time to Embed: Unlocking Foundation Models for Time Series with Channel Descriptions
Utsav Dutta, Sina Khoshfetrat Pakazad, Henrik Ohlsson
Traditional time series models are task-specific and often depend on dataset-specific training and extensive feature engineering. While Transformer-based architectures have improve…