2 citations · 4 across the 21 of their papers we have counts for
15 papers · 1 filter
Hessian Rank Constraint for Learning Structure of Nonlinear Latent Variable Models
Zijian Li, Ruichu Cai, Feng Xie +7
Uncovering latent variables and their causal relations from observed data is a fundamental yet challenging problem. Existing methods often rely on restrictive assumptions, such as…
Score-Based Causal Discovery of Latent Variable Causal Models
Ignavier Ng, Xinshuai Dong, Haoyue Dai +3
Identifying latent variables and the causal structure involving them is essential across various scientific fields. While many existing works fall under the category of constraint-…
The Power of Order: Fooling LLMs with Adversarial Table Permutations
Xinshuai Dong, Haifeng Chen, Xuyuan Liu +5
Large Language Models have achieved remarkable success and are increasingly deployed in critical applications involving tabular data, such as Table Question Answering. However, the…
Causal Representation Learning from General Environments under Nonparametric Mixing
Ignavier Ng, Shaoan Xie, Xinshuai Dong +2
Causal representation learning aims to recover the latent causal variables and their causal relations, typically represented by directed acyclic graphs (DAGs), from low-level obser…
Latent Variable Causal Discovery under Selection Bias
Haoyue Dai, Yiwen Qiu, Ignavier Ng +3
Addressing selection bias in latent variable causal discovery is important yet underexplored, largely due to a lack of suitable statistical tools: While various tools beyond basic…
Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models
Xinshuai Dong, Ignavier Ng, Haoyue Dai +4
Identifying the structure of a partially observed causal system is essential to various scientific fields. Recent advances have focused on constraint-based causal discovery to solv…