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NanoForecast v0.5: Competitive Time Series Forecasting Through Training Pipeline Optimization

Kishore, Gautam
arXiv (All) · Papers
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68t07i-2-6machine-learning
We present NanoForecast v0.5, a 6.5M-parameter forecaster that competes with models 31x its size (TimesFM, 200M parameters) after training pipeline fixes and no architecture change. Retraining the v0.3 architecture with corrected loss-scope handling, tensor shape alignment, and wider augmentation co
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