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Shohei Shimizu

Counterfactual Explanations of Black-box Machine Learning Models using Causal Discovery with Applications to Credit Rating

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Feb 05, 2024
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Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach

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Feb 02, 2024
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Use of Prior Knowledge to Discover Causal Additive Models with Unobserved Variables and its Application to Time Series Data

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Jan 18, 2024
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Scalable Counterfactual Distribution Estimation in Multivariate Causal Models

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Nov 02, 2023
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Causal-learn: Causal Discovery in Python

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Jul 31, 2023
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Discovery of Causal Additive Models in the Presence of Unobserved Variables

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Jun 04, 2021
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Causal Discovery with Multi-Domain LiNGAM for Latent Factors

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Sep 19, 2020
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Causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders

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Jan 14, 2020
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Analysis of Cause-Effect Inference via Regression Errors

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Feb 19, 2018
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Combining Linear Non-Gaussian Acyclic Model with Logistic Regression Model for Estimating Causal Structure from Mixed Continuous and Discrete Data

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Feb 16, 2018
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