activity
20202025
most citedFedDisco: Federated Learning with Discrepancy-Aware Collaboration

25 citations · 58 across the 22 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.LG2022

FedFM: Anchor-based Feature Matching for Data Heterogeneity in Federated Learning

Rui Ye, Zhenyang Ni, Chenxin Xu +3

One of the key challenges in federated learning (FL) is local data distribution heterogeneity across clients, which may cause inconsistent feature spaces across clients. To address…

cs.CV2022★ 1 cited

Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecasting

Bohan Tang, Yiqi Zhong, Chenxin Xu +5

In multi-modal multi-agent trajectory forecasting, two major challenges have not been fully tackled: 1) how to measure the uncertainty brought by the interaction module that causes…

cs.LG2022

Dynamic-Group-Aware Networks for Multi-Agent Trajectory Prediction with Relational Reasoning

Chenxin Xu, Yuxi Wei, Bohan Tang +3

Demystifying the interactions among multiple agents from their past trajectories is fundamental to precise and interpretable trajectory prediction. However, previous works mainly c…

cs.CV2022★ 7 cited

GroupNet: Multiscale Hypergraph Neural Networks for Trajectory Prediction with Relational Reasoning

Chenxin Xu, Maosen Li, Zhenyang Ni +2

Demystifying the interactions among multiple agents from their past trajectories is fundamental to precise and interpretable trajectory prediction. However, previous works only con…

cs.CV2022★ 9 cited

Remember Intentions: Retrospective-Memory-based Trajectory Prediction

Chenxin Xu, Weibo Mao, Wenjun Zhang +1

To realize trajectory prediction, most previous methods adopt the parameter-based approach, which encodes all the seen past-future instance pairs into model parameters. However, in…