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Found 4 papers, 2 papers with code
BiGCN: Leveraging Cell and Gene Similarities for Single-cell Transcriptome Imputation with Bi-Graph Convolutional Networks
In both the imputation and the cluster tasks, BiGCN consistently outperformed two variants of BiGCN that solely relied on either the gene co-expression graph or cell similarity graph.
Scalable Label Propagation for Multi-relational Learning on the Tensor Product of Graphs
In this paper, we generalize a widely used label propagation model to the normalized tensor product graph, and propose an optimization formulation and a scalable Low-rank Tensor-based Label Propagation algorithm (LowrankTLP) to infer multi-relations for two learning tasks, hyperlink prediction and multiple graph alignment.
Low-rank Label Propagation for Semi-supervised Learning with 100 Millions Samples
The success of semi-supervised learning crucially relies on the scalability to a huge amount of unlabelled data that are needed to capture the underlying manifold structure for better classification.
Network-based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis
Based on our observation that the abundances of the neighboring isoforms by domain-domain interactions in the network are positively correlated, Net-RSTQ models the expression of the neighboring transcripts as Dirichlet priors on the likelihood of the observed read alignments against the transcripts in one gene.
