6 papers
On the Recoverability of Causal Relations from Bulk Gene Expression Data
Gongxu Luo, Boyang Sun, Kun Zhang
Bulk gene expression profiling, which aggregates pooled RNA across cells within a biological sample, remains important in the single-cell era because it is typically less noisy, mo…
Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders
Gongxu Luo, Haoyue Dai, Loka Li +3
Gene regulatory network inference (GRNI) aims to discover how genes causally regulate each other from gene expression data. It is well-known that statistical dependencies in observ…
Permutation-Based Rank Test in the Presence of Discretization and Application in Causal Discovery with Mixed Data
Xinshuai Dong, Ignavier Ng, Boyang Sun +6
Recent advances have shown that statistical tests for the rank of cross-covariance matrices play an important role in causal discovery. These rank tests include partial correlation…
A Sample Efficient Conditional Independence Test in the Presence of Discretization
Boyang Sun, Yu Yao, Xinshuai Dong +4
In many real-world scenarios, interested variables are often represented as discretized values due to measurement limitations. Applying Conditional Independence (CI) tests directly…
An Analytical Emotion Framework of Rumour Threads on Social Media
Rui Xing, Boyang Sun, Kun Zhang +3
Rumours in online social media pose significant risks to modern society, motivating the need for better understanding of how they develop. We focus specifically on the interface be…
A Conditional Independence Test in the Presence of Discretization
Boyang Sun, Yu Yao, Guang-Yuan Hao +2
Testing conditional independence has many applications, such as in Bayesian network learning and causal discovery. Different test methods have been proposed. However, existing meth…