124 citations · 217 across the 23 of their papers we have counts for
23 papers
Subspace Identification for Multi-Source Domain Adaptation
Zijian Li, Ruichu Cai, Guangyi Chen +3
Multi-source domain adaptation (MSDA) methods aim to transfer knowledge from multiple labeled source domains to an unlabeled target domain. Although current methods achieve target…
Generalization bound for estimating causal effects from observational network data
Ruichu Cai, Zeqin Yang, Weilin Chen +2
Estimating causal effects from observational network data is a significant but challenging problem. Existing works in causal inference for observational network data lack an analys…
TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences
Yuequn Liu, Ruichu Cai, Wei Chen +5
Learning Granger causality from event sequences is a challenging but essential task across various applications. Most existing methods rely on the assumption that event sequences a…
Causal Discovery with Latent Confounders Based on Higher-Order Cumulants
Ruichu Cai, Zhiyi Huang, Wei Chen +2
Causal discovery with latent confounders is an important but challenging task in many scientific areas. Despite the success of some overcomplete independent component analysis (OIC…
Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences
Jie Qiao, Ruichu Cai, Siyu Wu +3
Learning causal structure among event types from discrete-time event sequences is a particularly important but challenging task. Existing methods, such as the multivariate Hawkes p…
A Survey on Causal Reinforcement Learning
Yan Zeng, Ruichu Cai, Fuchun Sun +2
While Reinforcement Learning (RL) achieves tremendous success in sequential decision-making problems of many domains, it still faces key challenges of data inefficiency and the lac…