Cai, Ruichu

48 publications

IJCAI 2025 Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism Ruichu Cai, Kaitao Zheng, Junxian Huang, Zijian Li, Zhengming Chen, Boyan Xu, Zhifeng Hao

IJCAI 2025 Causal-Aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting Wei Chen, Jiahao Zhang, Haipeng Zhu, Boyan Xu, Zhifeng Hao, Keli Zhang, Junjian Ye, Ruichu Cai

AAAI 2025 Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting Ruichu Cai, Haiqin Huang, Zhifan Jiang, Zijian Li, Changze Zhou, Yuequn Liu, Yuming Liu, Zhifeng Hao

AAAI 2025 Hypergraph Learning for Unsupervised Graph Alignment via Optimal Transport Yuguang Yan, Canlin Yang, Yuanlin Chen, Ruichu Cai, Michael Ng

ICML 2025 Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations Zhengming Chen, Yewei Xia, Feng Xie, Jie Qiao, Zhifeng Hao, Ruichu Cai, Kun Zhang

IJCAI 2025 Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning Ruichu Cai, Junjie Wan, Weilin Chen, Zeqin Yang, Zijian Li, Peng Zhen, Jiecheng Guo

ICLR 2025 On the Identification of Temporal Causal Representation with Instantaneous Dependence Zijian Li, Yifan Shen, Kaitao Zheng, Ruichu Cai, Xiangchen Song, Mingming Gong, Guangyi Chen, Kun Zhang

NeurIPS 2025 Online Time Series Forecasting with Theoretical Guarantees Zijian Li, Changze Zhou, Minghao Fu, Sanjay Manjunath, Fan Feng, Guangyi Chen, Yingyao Hu, Ruichu Cai, Kun Zhang

ICML 2025 Reducing Confounding Bias Without Data Splitting for Causal Inference via Optimal Transport Yuguang Yan, Zongyu Li, Haolin Yang, Zeqin Yang, Hao Zhou, Ruichu Cai, Zhifeng Hao

ICLR 2025 Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning Zijian Li, Shunxing Fan, Yujia Zheng, Ignavier Ng, Shaoan Xie, Guangyi Chen, Xinshuai Dong, Ruichu Cai, Kun Zhang

NeurIPS 2025 Towards Identifiability of Hierarchical Temporal Causal Representation Learning Zijian Li, Minghao Fu, Junxian Huang, Yifan Shen, Ruichu Cai, Yuewen Sun, Guangyi Chen, Kun Zhang

AAAI 2024 An Optimal Transport View for Subspace Clustering and Spectral Clustering Yuguang Yan, Zhihao Xu, Canlin Yang, Jie Zhang, Ruichu Cai, Michael Kwok-Po Ng

ICML 2024 Automating the Selection of Proxy Variables of Unmeasured Confounders Feng Xie, Zhengming Chen, Shanshan Luo, Wang Miao, Ruichu Cai, Zhi Geng

AAAI 2024 Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis Jie Qiao, Yu Xiang, Zhengming Chen, Ruichu Cai, Zhifeng Hao

MLOSS 2024 Causal-Learn: Causal Discovery in Python Yujia Zheng, Biwei Huang, Wei Chen, Joseph Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang

IJCAI 2024 Combinatorial Routing for Neural Trees Jiahao Li, Ruichu Cai, Yuguang Yan

ICML 2024 Doubly Robust Causal Effect Estimation Under Networked Interference via Targeted Learning Weilin Chen, Ruichu Cai, Zeqin Yang, Jie Qiao, Yuguang Yan, Zijian Li, Zhifeng Hao

AAAI 2024 Exploiting Geometry for Treatment Effect Estimation via Optimal Transport Yuguang Yan, Zeqin Yang, Weilin Chen, Ruichu Cai, Zhifeng Hao, Michael Kwok-Po Ng

ICML 2024 Feature Attribution with Necessity and Sufficiency via Dual-Stage Perturbation Test for Causal Explanation Xuexin Chen, Ruichu Cai, Zhengting Huang, Yuxuan Zhu, Julien Horwood, Zhifeng Hao, Zijian Li, José Miguel Hernández-Lobato

JMLR 2024 Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang

AAAI 2024 Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion Yuguang Yan, Yuanlin Chen, Shibo Wang, Hanrui Wu, Ruichu Cai

AAAI 2024 Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model Jie Qiao, Zhengming Chen, Jianhua Yu, Ruichu Cai, Zhifeng Hao

AAAI 2024 Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang

IJCAI 2024 Individual Causal Structure Learning from Population Data Wei Chen, Xiaokai Huang, Zijian Li, Ruichu Cai, Zhiyi Huang, Zhifeng Hao

NeurIPS 2024 Learning Discrete Latent Variable Structures with Tensor Rank Conditions Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang

NeurIPS 2024 On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function Yu Xiang, Jie Qiao, Zhefeng Liang, Zihuai Zeng, Ruichu Cai, Zhifeng Hao

ICML 2024 Reducing Balancing Error for Causal Inference via Optimal Transport Yuguang Yan, Hao Zhou, Zeqin Yang, Weilin Chen, Ruichu Cai, Zhifeng Hao

AAAI 2024 TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences Yuequn Liu, Ruichu Cai, Wei Chen, Jie Qiao, Yuguang Yan, Zijian Li, Keli Zhang, Zhifeng Hao

AAAI 2024 Where and How to Attack? a Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples Ruichu Cai, Yuxuan Zhu, Jie Qiao, Zefeng Liang, Furui Liu, Zhifeng Hao

ICML 2023 Causal Discovery with Latent Confounders Based on Higher-Order Cumulants Ruichu Cai, Zhiyi Huang, Wei Chen, Zhifeng Hao, Kun Zhang

IJCAI 2023 Some General Identification Results for Linear Latent Hierarchical Causal Structure Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Ruichu Cai

IJCAI 2023 Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences Jie Qiao, Ruichu Cai, Siyu Wu, Yu Xiang, Keli Zhang, Zhifeng Hao

NeurIPS 2023 Subspace Identification for Multi-Source Domain Adaptation Zijian Li, Ruichu Cai, Guangyi Chen, Boyang Sun, Zhifeng Hao, Kun Zhang

AAAI 2022 Identification of Linear Latent Variable Model with Arbitrary Distribution Zhengming Chen, Feng Xie, Jie Qiao, Zhifeng Hao, Kun Zhang, Ruichu Cai

AAAI 2021 Appearance-Motion Memory Consistency Network for Video Anomaly Detection Ruichu Cai, Hao Zhang, Wen Liu, Shenghua Gao, Zhifeng Hao

IJCAI 2021 Causal Discovery with Multi-Domain LiNGAM for Latent Factors Yan Zeng, Shohei Shimizu, Ruichu Cai, Feng Xie, Michio Yamamoto, Zhifeng Hao

NeurIPS 2021 Domain Adaptation with Invariant Representation Learning: What Transformations to Learn? Petar Stojanov, Zijian Li, Mingming Gong, Ruichu Cai, Jaime G. Carbonell, Kun Zhang

NeurIPS 2021 SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL Ruichu Cai, Jinjie Yuan, Boyan Xu, Zhifeng Hao

AAAI 2021 Time Series Domain Adaptation via Sparse Associative Structure Alignment Ruichu Cai, Jiawei Chen, Zijian Li, Wei Chen, Keli Zhang, Junjian Ye, Zhuozhang Li, Xiaoyan Yang, Zhenjie Zhang

NeurIPS 2020 Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang

IJCAI 2019 Causal Discovery with Cascade Nonlinear Additive Noise Model Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, Zhifeng Hao

IJCAI 2019 Learning Disentangled Semantic Representation for Domain Adaptation Ruichu Cai, Zijian Li, Pengfei Wei, Jie Qiao, Kun Zhang, Zhifeng Hao

NeurIPS 2019 Triad Constraints for Learning Causal Structure of Latent Variables Ruichu Cai, Feng Xie, Clark Glymour, Zhifeng Hao, Kun Zhang

IJCAI 2018 An Encoder-Decoder Framework Translating Natural Language to Database Queries Ruichu Cai, Boyan Xu, Zhenjie Zhang, Xiaoyan Yang, Zijian Li, Zhihao Liang

NeurIPS 2018 Causal Discovery from Discrete Data Using Hidden Compact Representation Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, Zhifeng Hao

AAAI 2018 SELF: Structural Equational Likelihood Framework for Causal Discovery Ruichu Cai, Jie Qiao, Zhenjie Zhang, Zhifeng Hao

IJCAI 2017 A Robust Noise Resistant Algorithm for POI Identification from Flickr Data Yiyang Yang, Zhiguo Gong, Qing Li, Leong Hou U, Ruichu Cai, Zhifeng Hao

ICML 2013 SADA: A General Framework to Support Robust Causation Discovery Ruichu Cai, Zhenjie Zhang, Zhifeng Hao