The Joint Causal Effect in Linear Structural Equation Model and Its Application to Process Analysis. - Manabu Kuroki; Zhihong Cai (AISTATS, 2003)

Selection of Identifiability Criteria for Total Effects by using Path Diagrams. - Manabu Kuroki; Zhihong Cai (UAI, 2004)

Instrumental variable tests for Directed Acyclic Graph Models. - Manabu Kuroki; Zhihong Cai (AISTATS, 2005)

Counterfactual Reasoning in Linear Structural Equation Models. - Zhihong Cai; Manabu Kuroki (UAI, 2005)

The Graphical Identification for Total Effects by using Surrogate Variables. - Manabu Kuroki; Zhihong Cai; Hiroki Motogaito (UAI, 2005)

Stratified Analysis of 'Probabilities of Causation'. - Manabu Kuroki; Zhihong Cai (UAI, 2006)

Evaluation of the Causal Effect of Control Plans in Nonrecursive Structural Equation Models. - Manabu Kuroki; Zhihong Cai (UAI, 2007)

On Identifying Total Effects in the Presence of Latent Variables and Selection bias. - Zhihong Cai; Manabu Kuroki (UAI, 2008)

Using Descendants as Instrumental Variables for the Identification of Direct Causal Effects in Linear SEMs. - Hei Chan; Manabu Kuroki (AISTATS, 2010)

Identification of Causal Effects in Linear SEMs using the Instrumental Variable Function. - Hei Chan; Manabu Kuroki (ISAIM, 2012)

The Evaluation of Causal Effects in Studies with an Unobserved Exposure/Outcome Variable: Bounds and Identification - Manabu Kuroki; Zhihong Cai (CoRR, 2012)

On Estimating Causal Effects based on Supplemental Variables. - Takahiro Hayashi; Manabu Kuroki (AISTATS, 2014)

Learning Maximal Ancestral Graphs with Robustness for Faithfulness Violations. - Takashi Isozaki; Manabu Kuroki (AMBN@JSAI-isAI, 2015)

Learning Causal Graphs with Latent Confounders in Weak Faithfulness Violations. - Takashi Isozaki; Manabu Kuroki (New Gener. Comput., 2017)

Identification and Estimation of Joint Probabilities of Potential Outcomes in Observational Studies with Covariate Information. - Ryusei Shingaki; Manabu Kuroki (NeurIPS, 2021)

Exact variance formula for the estimated mean outcome with external intervention based on the front-door criterion in Gaussian linear structural equation models. - Hisayoshi Nanmo; Manabu Kuroki (J. Multivar. Anal., 2021)

Partially adaptive regularized multiple regression analysis for estimating linear causal effects. - Hisayoshi Nanmo; Manabu Kuroki (UAI, 2022)

Identification and Estimation of the Probabilities of Potential Outcome Types Using Covariate Information in Studies with Non-compliance. - Yuta Kawakami; Ryusei Shingaki; Manabu Kuroki (AAAI, 2023)

Probabilities of Potential Outcome Types in Experimental Studies: Identification and Estimation Based on Proxy Covariate Information. - Ryusei Shingaki; Manabu Kuroki (AAAI, 2023)

Instrumental Variable Estimation of Average Partial Causal Effects. - Yuta Kawakami; Manabu Kuroki; Jin Tian (ICML, 2023)

An unbiased estimator of the causal effect on the variance based on the back-door criterion in Gaussian linear structural equation models. - Taiki Tezuka; Manabu Kuroki (J. Multivar. Anal., 2023)

Identification and Estimation of "Causes of Effects" using Covariate-Mediator Information. - Ryusei Shingaki; Manabu Kuroki (AISTATS, 2024)

Proportion-based Sensitivity Analysis of Uncontrolled Confounding Bias in Causal Inference. - Haruka Yoshida; Manabu Kuroki (IJCAI, 2024)

New Proportion Measures of Discrimination Based on Natural Direct and Indirect Effects. - Ryusei Shingaki; Manabu Kuroki (ISAIM, 2024)

Probabilities of Causation for Continuous and Vector Variables. - Yuta Kawakami; Manabu Kuroki; Jin Tian (UAI, 2024)

Identification and Estimation of Conditional Average Partial Causal Effects via Instrumental Variable. - Yuta Kawakami; Manabu Kuroki; Jin Tian (UAI, 2024)

PCM Selector: Penalized Covariate-Mediator Selection Operator for Evaluating Linear Causal Effects. - Hisayoshi Nanmo; Manabu Kuroki (AAAI, 2025)