Time Series Isn’t Enough: How Graph Neural Networks Change...

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2026-01-19 12:01:01 -

Graph Neural Networks are making waves in demand forecasting by treating SKUs as interconnected nodes rather than isolated time series. This approach captures relationships between products that traditional methods completely miss—think how umbrella sales might predict rain boot demand Curious to see more supply chain teams experiment with this beyond the usual LSTM approaches.

Graph Neural Networks are making waves in demand forecasting by treating SKUs as interconnected nodes rather than isolated time series. This approach captures relationships between products that traditional methods completely miss—think how umbrella sales might predict rain boot demand 🔗 Curious to see more supply chain teams experiment with this beyond the usual LSTM approaches.

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Time Series Isn’t Enough: How Graph Neural Networks Change Demand Forecasting

Why modeling SKUs as a network reveals what traditional forecasts miss The post Time Series Isn’t Enough: How Graph Neural Networks Change Demand Forecasting appeared first on Towards Data Science.

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