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FlowTSFM: Turning Encoder Depth into Quantile Transport

Abdessalem, Bahaeddine et al.
arXiv (OAI Expanded) · Papers
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machine-learning
Encoder-based time series foundation models (TSFMs) typically rely on deep stacks of independently parameterized Transformer layers, where only the final forecast is supervised and intermediate representations have no explicit predictive role. We introduce FlowTSFM, an encoder architecture that inte
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