activity
20192022
most citedDiscriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment

2 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO20221 cited

Ensemble diverse hypotheses and knowledge distillation for unsupervised cross-subject adaptation

Kuangen Zhang, Jiahong Chen, Jing Wang +4

Recognizing human locomotion intent and activities is important for controlling the wearable robots while walking in complex environments. However, human-robot interface signals ar…

cs.LG20222 cited

Preserving Domain Private Representation via Mutual Information Maximization

Jiahong Chen, Jing Wang, Weipeng Lin +2

Recent advances in unsupervised domain adaptation have shown that mitigating the domain divergence by extracting the domain-invariant representation could significantly improve the…

eess.SP2022

Data-driven Sensor Deployment for Spatiotemporal Field Reconstruction

Jiahong Chen

This paper concerns the data-driven sensor deployment problem in large spatiotemporal fields. Traditionally, sensor deployment strategies have been heavily dependent on model-based…

cs.CV20202 cited

Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment

Jing Wang, Jiahong Chen, Jianzhe Lin +2

In this study, we focus on the unsupervised domain adaptation problem where an approximate inference model is to be learned from a labeled data domain and expected to generalize we…

eess.SP20191 cited

Optimization of Wireless Sensor Network Deployment for Spatiotemporal Reconstruction and Prediction

Jiahong Chen, Teng Li, Jing Wang +1

This paper addresses the problem of optimizing sensor deployment locations to reconstruct and also predict a spatiotemporal field. A novel deep learning framework is developed to f…