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M. Alsamhi

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Conference Aug 2026

SemTFT: When Semantics Meet Intermittent Demand Forecasting

The extreme sparsity, zero inflation, and weak temporal regularity inherent to intermittent demand forecasting make it difficult to use traditional deep learning models. This paper presents a novel framework called SemTFT, a conditional semantic-temporal fusion transformer, which incorporates semantic information in a...

Halimah Alkhorasani, M. Alsamhi, A. V. Shvetsov · 0 citations

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