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Federated learning from molecules to processes: A perspective
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DOI：10.1016/j.cherd.2026.07.011.png)
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Abstract
En 中文
• Federated learning for joint training of ML models by chemical companies. • Addressing data scarcity in chemical and process data. • Data heterogeneity in the chemical industry. • Advancing ML models in industrial collaborations without data sharing.
Keywords:
Machine learning
Data privacy
Graph neural networks
Chemical industry
Collaboration
Federated learning
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