The following publications are possibly variants of this publication: 
- DisenCDR: Learning Disentangled Representations for Cross-Domain RecommendationJiangxia Cao, Xixun Lin, Xin Cong, Jing Ya, Tingwen Liu, Bin Wang 0004. sigir 2022: 267-277 [doi] 
- Disentangled Representations for Cross-Domain Recommendation via Heterogeneous Graph Contrastive LearningXinyue Liu, Bohan Li 0001, Yijun Chen, Xiaoxue Li, Shuai Xu, Hongzhi Yin. dasfaa 2025: 35-50 [doi] 
- Learning Disentangled Representations for RecommendationJianxin Ma, Chang Zhou, Peng Cui 0001, Hongxia Yang, Wenwu Zhu 0001. nips 2019: 5712-5723 [doi] 
- Disentangled Multi-Graph Convolution for Cross-Domain RecommendationYibo Gao, Zhen Liu, Xinxin Yang, Sibo Lu, Yafan Yuan. tkdd, 19(3), April 2025.  [doi] 
- Learning disentangled representations in the imaging domainXiao Liu, Pedro Sanchez, Spyridon Thermos, Alison Q. O'Neil, Sotirios A. Tsaftaris. mia, 80:102516, 2022.  [doi] 
- IDC-CDR: Cross-domain Recommendation based on Intent Disentanglement and Contrast LearningJing Xu, Mingxin Gan, Hang Zhang, Shuhao Zhang. ipm, 61(6):103871, 2024.  [doi] 
- Graph Disentangled Contrastive Learning with Personalized Transfer for Cross-Domain RecommendationJing Liu, Lele Sun, Weizhi Nie, Peiguang Jing, Yuting Su 0001. AAAI 2024: 8769-8777 [doi]