Causal discovery for observational sciences using supervised machine learning

25 February 2022

Papers citing "Causal discovery for observational sciences using supervised machine learning"

9 / 9 papers shown

Title
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning Jiaru Zhang Rui Ding Qiang Fu Bojun Huang Zizhen Deng Yang Hua Haibing Guan Shi Han Dongmei Zhang CML 46 0 0 15 Feb 2025
Embracing the black box: Heading towards foundation models for causal discovery from time series data Gideon Stein M. Shadaydeh Joachim Denzler CML AI4TS 10 1 0 14 Feb 2024
Sample, estimate, aggregate: A recipe for causal discovery foundation models Menghua Wu Yujia Bao Regina Barzilay Tommi Jaakkola CML 41 7 0 02 Feb 2024
Learned Causal Method Prediction Shantanu Gupta Cheng Zhang Agrin Hilmkil OOD 31 2 0 07 Nov 2023
Causal Discovery from Temporal Data: An Overview and New Perspectives Chang Gong Di Yao Chuzhe Zhang Wenbin Li Jingping Bi AI4TS CML 16 17 0 17 Mar 2023
On the Unlikelihood of D-Separation Itai Feigenbaum Haiquan Wang Shelby Heinecke Juan Carlos Niebles Weiran Yao Caiming Xiong Devansh Arpit CML 18 1 0 10 Mar 2023
Log-Paradox: Necessary and sufficient conditions for confounding statistically significant pattern reversal under the log-transform Ben Cardoen Hanene Ben Yedder Sieun Lee I. Nabi Ghassan Hamarneh MedIm 40 0 0 09 Feb 2023
Learning Sparse Nonparametric DAGs Xun Zheng Chen Dan Bryon Aragam Pradeep Ravikumar Eric P. Xing CML 101 258 0 29 Sep 2019
Causal Inference and Causal Explanation with Background Knowledge Christopher Meek CML 216 626 0 20 Feb 2013