A heterogeneous graph cross-omics attention model for single-cell representation learning.
Yue LiuJunfeng ZhangShulin WangWei ZhangXiangxiang ZengChee Keong KwohPublished in: BIBM (2022)
Keyphrases
- computational model
- graph representation
- learning systems
- graph model
- reinforcement learning
- learning algorithm
- graphical representation
- mathematical model
- markov random field
- probability distribution
- feature selection
- fully connected
- management system
- learned models
- qualitative models
- neural network
- high level
- graph mining
- learning models
- learning tasks
- statistical model
- learning process
- prior knowledge
- probabilistic model
- parameter estimation
- online learning