FedDis: A Causal Disentanglement Framework for Federated Traffic Prediction
FedDis: A Causal Disentanglement Framework for Federated Traffic Prediction explores FedDis uses causal disentanglement to improve federated traffic prediction under non-IID data conditions.. Commercial viability score: 5/10 in Federated Learning.
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