most citedReputation-Driven Asynchronous Federated Learning for Enhanced Trajectory Prediction with Blockchain

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2024

MFF-FTNet: Multi-scale Feature Fusion across Frequency and Temporal Domains for Time Series Forecasting

Yangyang Shi, Qianqian Ren, Yong Liu +1

Time series forecasting is crucial in many fields, yet current deep learning models struggle with noise, data sparsity, and capturing complex multi-scale patterns. This paper prese…

cs.LG2024★ 1 cited

Reputation-Driven Asynchronous Federated Learning for Enhanced Trajectory Prediction with Blockchain

Weiliang Chen, Li Jia, Yang Zhou +1

Federated learning combined with blockchain empowers secure data sharing in autonomous driving applications. Nevertheless, with the increasing granularity and complexity of vehicle…