Unsupervised Domain Adaptation for Multimodal Mobile Sensing with Multi-Branch Adversarial Training

Multimodal mobile sensing data exhibits distribution shifts across different domains, hindering the deployment of models in real-world scenarios. This paper proposes a novel multi-branch adversarial training approach, M3BAT, to effectively adapt models to unseen target domains in an unsupervised manner.