Article
Automation & Control Systems
Hao Zhang, Shuigeng Zhou, Chuanxu Yan, Jihong Guan, Xin Wang, Ji Zhang, Jun Huan
Summary: This article addresses two important issues in causal inference in high-dimensional situations: reducing redundant CI tests and constructing the true causal graph. The proposed methods, including recursive decomposition and regression-based CI tests, can effectively solve these problems.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Statistics & Probability
Gonzalo Vazquez-Bare
Summary: This study proposes a potential outcomes framework to analyze spillover effects using instrumental variables. The findings suggest that intention-to-treat (ITT) parameters do not have a clear link to causally interpretable parameters, and rescaling them by first-stage estimands recovers a weighted combination of average effects. The study also analyzes the identification of causal effects under one-sided noncompliance and introduces an alternative assumption for identifying parameters of interest under two-sided noncompliance.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2023)
Article
Computer Science, Artificial Intelligence
Jie Qiao, Ruichu Cai, Kun Zhang, Zhenjie Zhang, Zhifeng Hao
Summary: The article discusses the identification of causal direction between a causal-effect pair from observed data, proposing a confounding cascade nonlinear additive noise model to address the issue of omitted latent causal variables. Simulation results demonstrate the method's ability to identify indirect causal relations across various settings, while experimental results suggest that the proposed model and method greatly extend the applicability of causal discovery based on functional causal models in nonlinear cases.
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
(2021)
Article
Computer Science, Information Systems
Boxiang Zhao, Shuliang Wang, Lianhua Chi, Qi Li, Xiaojia Liu, Jing Geng
Summary: This study proposes a new graph structure called Causal Star Graph (CSG) and a corresponding framework called Causal Discovery via Causal Star Graphs (CD-CSG) to address the limitations of existing causal discovery methods. By conducting generalized learning in CSGs, the causal directions in directed acyclic graphs can be accurately identified. Experimental results show that CD-CSG can effectively identify causal relationships between variables and outperforms existing models in terms of accuracy.
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
(2023)
Article
Statistics & Probability
Fatemeh Asgari, Mohammad Hossein Alamatsaz
Summary: This article shows that the entropy power inequality (EPI) holds for the case when the involved random variables are dependent, under some conditions. A lower bound for the Fisher information of the output signal is obtained, which is useful on its own. An example is provided to illustrate the result.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2022)
Article
Robotics
Ruimin Chen, Yan Lu, Paul Witherell, Timothy W. Simpson, Soundar Kumara, Hui Yang
Summary: An ontology-based Bayesian network model is proposed in the study to represent the causal relationships between additive manufacturing parameters and quality assurance/quality control requirements, which enables engineering interpretations and advances the monitoring and control of additive manufacturing processes.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Public, Environmental & Occupational Health
Fernando Pires Hartwig, Linbo Wang, George Davey Smith, Neil Martin Davies
Summary: Instrumental variables (IVs) can be used to determine the causal effect of a treatment X on an outcome Y. Further assumptions, such as homogeneity in the causal effect of X on Y and no effect modification, are needed to identify the average causal effect (ACE) of X on Y. The assumption of no simultaneous heterogeneity is sufficient for identifying the ACE using IVs, even if other assumptions are violated.
Article
Computer Science, Information Systems
Aiguo Wang, Li Liu, Jiaoyun Yang, Lian Li
Summary: This paper discusses certain issues related to nonlinear causality and introduces the concept of causality field as well as analysis methods for nonlinear causality. The importance of nonlinear causality in handling complex causal inference problems is demonstrated through specific examples.
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Debo Cheng, Jiuyong Li, Lin Liu, Kui Yu, Thuc Duy Le, Jixue Liu
Summary: Instrumental variable (IV) is a powerful method for inferring causal effects from observational data. However, the selection of a valid IV is crucial as an invalid IV can result in biased estimates. In this article, a data-driven algorithm is proposed to discover valid IVs based on partial ancestral graphs (PAGs). Experiments on synthetic and real-world datasets demonstrate that the algorithm provides accurate estimates of causal effects compared to state-of-the-art IV-based estimators.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Information Systems
Hao Zhang, Chuanxu Yan, Shuigeng Zhou, Jihong Guan, Ji Zhang
Summary: This paper introduces a new method for discovering combined causes in causal systems, categorizing them into three types with formal definitions and extending the additive noise model for inference. The research shows that a candidate variable set constitutes a combined cause if it allows ANM only in the forward direction and does not contain disturbance variables.
INFORMATION SCIENCES
(2021)
Article
Engineering, Electrical & Electronic
Luca Arcangeloni, Enrico Testi, Andrea Giorgetti
Summary: Detecting reactive jammers in wireless networks is a challenge. This study proposes a novel framework using external RF sensors to detect reactive jamming. It relies on an underdetermined blind source separation method and a jamming detection based on causal inference. The framework is applied to a LoRa-based IoT system and outperforms existing methods in the presence of shadowing.
IEEE TRANSACTIONS ON COMMUNICATIONS
(2023)
Article
Statistics & Probability
Raj Agrawal, Chandler Squires, Neha Prasad, Caroline Uhler
Summary: Many real-world decision-making tasks require learning causal relationships between a set of variables. Traditional causal discovery methods, however, require that all variables are observed, which is often not feasible in practical scenarios. In this article, we present a provably consistent method to estimate causal relationships in the nonlinear, pervasive confounding setting by utilizing additional structure among the confounders and considering both confounders and nonlinear effects explicitly.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Alexandre Bazin, Miguel Couceiro, Marie-Dominique Devignes, Amedeo Napoli
Summary: Efficiently discovering and representing causal relations in science is an important problem, and this paper proposes an adaptation of the Formal Concept Analysis formalism for this purpose.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2022)
Article
Biology
Guillem Hernandez Guillamet, Francesc Lopez Segui, Josep Vidal-Alaball, Beatriz Lopez
Summary: This study introduces a new approach, CauRuler, which deals with causality using association rules and a pruning strategy to reduce the size of the rule set, making it suitable for healthcare practice. The method controls more confounders, avoiding spurious associations, and obtains complex and general causal paths.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Allergy
Helena Bui, Amena Keshawarz, Shih-Jen Hwang, Chen Yao, Gha Young Lee, Kathryn Recto, George T. O'Connor, Daniel Levy
Summary: Through this genomic approach, we identified sRAGE as a putatively causal, biologically important, and protective protein in relation to asthma.
JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY
(2022)
Article
Oncology
Wei Feng, Xianling Guo, Haidong Huang, Chang Xu, Yutao Li, Shicheng Guo, Zhenghong Zhao, Qiang Li, Daru Lu, Li Jin, Jiucun Wang, Gengxi Jiang, Junjie Wu
CURRENT PROBLEMS IN CANCER
(2019)
Letter
Rheumatology
Jing Liu, Weilin Pu, Yuan Li, Yanyun Ma, Qi Zhu, Wei Wan, Chengde Yang, Xiaofeng Wang, Xingdong Chen, Xiaodong Zhou, John D. Reveille, Li Jin, Hejian Zou, Jiucun Wang
ANNALS OF THE RHEUMATIC DISEASES
(2019)
Article
Gastroenterology & Hepatology
Zhenqiu Liu, Yanfeng Jiang, Huangbo Yuan, Qiwen Fang, Ning Cai, Chen Suo, Li Jin, Tiejun Zhang, Xingdong Chen
JOURNAL OF HEPATOLOGY
(2019)
Article
Genetics & Heredity
Weiyu Li, Xiaojin He, Shenmin Yang, Chunyu Liu, Huan Wu, Wangjie Liu, Mingrong Lv, Dongdong Tang, Jing Tan, Shuyan Tang, Yujie Chen, Jiajia Wang, Zhiguo Zhang, Hongyan Wang, Li Jin, Feng Zhang, Yunxia Cao
JOURNAL OF HUMAN GENETICS
(2019)
Article
Genetics & Heredity
Xiaojin He, Weiyu Li, Huan Wu, Mingrong Lv, Wangjie Liu, Chunyu Liu, Fuxi Zhu, Caihua Li, Youyan Fang, Chenyu Yang, Huiru Cheng, Junqiang Zhang, Jing Tan, Tingting Chen, Dongdong Tang, Bing Song, Xue Wang, Xiaomin Zha, Hongyan Wang, Zhaolian Wei, Shenmin Yang, Hexige Saiyin, Ping Zhou, Li Jin, Jian Wang, Zhiguo Zhang, Feng Zhang, Yunxia Cao
JOURNAL OF MEDICAL GENETICS
(2019)
Article
Geriatrics & Gerontology
S. Yao, J. Guo, G. Shi, Y. Zhu, Y. Wang, X. Chu, X. Jiang, L. Jin, Z. Wang, X. Wang
JOURNAL OF NUTRITION HEALTH & AGING
(2019)
Article
Biochemistry & Molecular Biology
Shuangshuang Dong, Chunyan Wang, Xueping Li, Qian Shen, Xiaoyi Fu, Mingyan Wu, Chengcheng Song, Nan Yang, Yanhua Wu, Hongyan Wang, Li Jin, Hong Xu, Feng Zhang
MOLECULAR GENETICS AND GENOMICS
(2019)
Article
Biochemistry & Molecular Biology
Ying Yu, Yunjin Wang, Zhaojie Xia, Xiangyu Zhang, Kailiang Jin, Jingcheng Yang, Luyao Ren, Zheng Zhou, Dong Yu, Tao Qing, Chengdong Zhang, Li Jin, Yuanting Zheng, Li Guo, Leming Shi
NUCLEIC ACIDS RESEARCH
(2019)
Article
Public, Environmental & Occupational Health
Zhenqiu Liu, Qin Yang, Ning Cai, Li Jin, Tiejun Zhang, Xingdong Chen
AMERICAN JOURNAL OF EPIDEMIOLOGY
(2019)
Article
Medicine, Research & Experimental
Qingmei Liu, Jiaying Lu, Jinran Lin, Yulong Tang, Weilin Pu, Xiangguang Shi, Shuai Jiang, Jing Liu, Yanyun Ma, Yuan Li, Jinhua Xu, Li Jin, Jiucun Wang, Wenyu Wu
BIOMEDICINE & PHARMACOTHERAPY
(2019)
Article
Hematology
Shicheng Guo, Shuai Jiang, Narendranath Epperla, Yanyun Ma, Mehdi Maadooliat, Zhan Ye, Brent Olson, Minghua Wang, Terrie Kitchner, Jeffrey Joyce, Peng An, Fudi Wang, Robert Strenn, Joseph J. Mazza, Jennifer K. Meece, Wenyu Wu, Li Jin, Judith A. Smith, Jiucun Wang, Steven J. Schrodi
Article
Oncology
Zhenqiu Liu, Chunqing Lin, Lina Mu, Chen Suo, Weimin Ye, Li Jin, Silvia Franceschi, Tiejun Zhang, Xingdong Chen
INTERNATIONAL JOURNAL OF CANCER
(2020)
Article
Genetics & Heredity
Jian Mu, Wenjing Wang, Biaobang Chen, Ling Wu, Bin Li, Xiaoyan Mao, Zhihua Zhang, Jing Fu, Yanping Kuang, Xiaoxi Sun, Qiaoli Li, Li Jin, Lin He, Qing Sang, Lei Wang
JOURNAL OF MEDICAL GENETICS
(2019)
Article
Oncology
Chen Suo, Yajun Yang, Ziyu Yuan, Tiejun Zhang, Xiaorong Yang, Tao Qing, Pei Gao, Leming Shi, Min Fan, Hongwei Cheng, Ming Lu, Li Jin, Xingdong Chen, Weimin Ye
JOURNAL OF THORACIC ONCOLOGY
(2019)
Article
Neuroimaging
Yingzhe Wang, Yanfeng Jiang, Chen Suo, Ziyu Yuan, Kelin Xu, Qi Yang, Weijun Tang, Kexun Zhang, Zhen Zhu, Weizhong Tian, Min Fan, Shuyuan Li, Weimin Ye, Qiang Dong, Li Jin, Mei Cui, Xingdong Chen
NEUROIMAGE-CLINICAL
(2019)