Learning Sparse Causal Models is not NP-hard

26 September 2013

Joris Mooij

Papers citing "Learning Sparse Causal Models is not NP-hard"

50 / 53 papers shown

Title
Constraint-based causal discovery with tiered background knowledge and latent variables in single or overlapping datasets Christine W. Bang Vanessa Didelez CML 160 0 0 27 Mar 2025
Differentiable Causal Discovery For Latent Hierarchical Causal Models Parjanya Prashant Ignavier Ng Kun Zhang Zhen Zhang CML 338 0 0 29 Nov 2024
Causal Discovery with Fewer Conditional Independence Tests Kirankumar Shiragur Jiaqi Zhang Caroline Uhler CML 56 2 0 03 Jun 2024
Local Causal Structure Learning in the Presence of Latent Variables Feng Xie Zheng Li Peng Wu Yan Zeng Chunchen Liu Zhi Geng CML 90 2 0 25 May 2024
Local Causal Discovery for Structural Evidence of Direct Discrimination Jacqueline R. M. A. Maasch Kyra Gan Violet Chen Agni Orfanoudaki Nil-Jana Akpinar Fei Wang 68 2 0 23 May 2024
Membership Testing in Markov Equivalence Classes via Independence Query Oracles Jiaqi Zhang Kirankumar Shiragur Caroline Uhler CML 73 0 0 09 Mar 2024
Generalization of LiNGAM that allows confounding Joe Suzuki Tian-Le Yang 77 1 0 30 Jan 2024
Causal Interpretation of Self-Attention in Pre-Trained Transformers R. Y. Rohekar Yaniv Gurwicz Shami Nisimov MILM 60 19 0 31 Oct 2023
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs Jacqueline R. M. A. Maasch Weishen Pan Shantanu Gupta Volodymyr Kuleshov Kyra Gan Fei Wang 81 7 0 25 Oct 2023
Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets Tiago da Silva Eliezer de Souza da Silva Adèle H. Ribeiro António Góis Dominik Heider Samuel Kaski Diego Mesquita CML 128 7 0 21 Sep 2023
s-ID: Causal Effect Identification in a Sub-Population Amir Mohammad Abouei Ehsan Mokhtarian Negar Kiyavash CML 53 3 0 05 Sep 2023
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables Feng Xie Erdun Gao Zhen Chen Ruichu Cai Clark Glymour Zhi Geng Kun Zhang CML 46 7 0 13 Aug 2023
Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge Abhin Shah Karthikeyan Shanmugam Murat Kocaoglu CML 77 7 0 19 Jun 2023
DRCFS: Doubly Robust Causal Feature Selection Francesco Quinzan Ashkan Soleymani Patrik Jaillet C. Rojas Stefan Bauer 107 13 0 12 Jun 2023
From Temporal to Contemporaneous Iterative Causal Discovery in the Presence of Latent Confounders R. Y. Rohekar Shami Nisimov Yaniv Gurwicz Gal Novik CML 44 11 0 01 Jun 2023
Toward Falsifying Causal Graphs Using a Permutation-Based Test Elias Eulig Atalanti A. Mastakouri Patrick Blobaum Michael W. Hardt Dominik Janzing 35 13 0 16 May 2023
Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning Matthew Ashman Chao Ma Agrin Hilmkil Joel Jennings Cheng Zhang CML AI4CE 93 10 0 22 Mar 2023
Weak equivalence of local independence graphs Søren Wengel Mogensen 79 3 0 24 Feb 2023
$Interpretability and causal discovery of the machine learning models to predict the production of CBM wells after hydraulic fracturing$ Interpretability and causal discovery of the machine learning models to predict the production of CBM wells after hydraulic fracturing Chao Min Guo-quan Wen Liang Gou Xiaogang Li Zhaozhong Yang CML 39 12 0 21 Dec 2022
CLEAR: Causal Explanations from Attention in Neural Recommenders Shami Nisimov R. Y. Rohekar Yaniv Gurwicz G. Koren Gal Novik CML 30 6 0 07 Oct 2022
Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables Ehsan Mokhtarian M. Khorasani Jalal Etesami Negar Kiyavash CML 83 7 0 14 Aug 2022
Causal Structure Learning: a Combinatorial Perspective C. Squires Caroline Uhler CML 120 47 0 02 Jun 2022
Differentiable Causal Discovery Under Latent Interventions Gonccalo R. A. Faria André F. T. Martins Mário A. T. Figueiredo BDL CML OOD 89 23 0 04 Mar 2022
Local Constraint-Based Causal Discovery under Selection Bias Philip Versteeg Cheng Zhang Joris M. Mooij CML 58 14 0 03 Mar 2022
Learning Bayesian Networks in the Presence of Structural Side Information Ehsan Mokhtarian S. Akbari Fatemeh Jamshidi Jalal Etesami Negar Kiyavash 67 16 0 20 Dec 2021
Iterative Causal Discovery in the Possible Presence of Latent Confounders and Selection Bias R. Y. Rohekar Shami Nisimov Yaniv Gurwicz Gal Novik CML 173 26 0 07 Nov 2021
Recursive Causal Structure Learning in the Presence of Latent Variables and Selection Bias S. Akbari Ehsan Mokhtarian AmirEmad Ghassami Negar Kiyavash CML 59 26 0 22 Oct 2021
A survey of Bayesian Network structure learning N. K. Kitson Anthony C. Constantinou Zhi-gao Guo Yang Liu Kiattikun Chobtham CML 106 198 0 23 Sep 2021
Improving Efficiency and Accuracy of Causal Discovery Using a Hierarchical Wrapper Shami Nisimov Yaniv Gurwicz R. Y. Rohekar Gal Novik CML TPM 18 6 0 11 Jul 2021
Identifiability of AMP chain graph models Yuhao Wang Arnab Bhattacharyya CML 22 0 0 17 Jun 2021
Definite Non-Ancestral Relations and Structure Learning Wenyu Chen Mathias Drton Ali Shojaie CML 47 1 0 20 May 2021
Causal Inference in medicine and in health policy, a summary Wenhao Zhang Ramin Ramezani A. Naeim CML OOD 76 6 0 10 May 2021
Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding Alexis Bellot M. Schaar CML 75 11 0 28 Mar 2021
FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders Wei Chen Kun Zhang Ruichu Cai Erdun Gao Joseph Ramsey Zijian Li Clark Glymour CML 50 11 0 26 Mar 2021
Identification of Latent Variables From Graphical Model Residuals B. Hayete Fred Gruber Anna Decker R. Yan CML 106 0 0 07 Jan 2021
A Single Iterative Step for Anytime Causal Discovery R. Y. Rohekar Yaniv Gurwicz Shami Nisimov Gal Novik CML 26 1 0 14 Dec 2020
Causal Feature Selection via Orthogonal Search Ashkan Soleymani Anant Raj Stefan Bauer Bernhard Schölkopf M. Besserve CML 91 17 0 06 Jul 2020
Distributional robustness of K-class estimators and the PULSE M. E. Jakobsen J. Peters OOD 70 29 0 07 May 2020
Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles Joris M. Mooij Tom Claassen 93 42 0 01 May 2020
Towards unique and unbiased causal effect estimation from data with hidden variables Debo Cheng Jiuyong Li Lin Liu Kui Yu T. Le Jixue Liu CML 55 0 0 24 Feb 2020
Ordering-Based Causal Structure Learning in the Presence of Latent Variables D. Bernstein Basil Saeed C. Squires Caroline Uhler CML 71 42 0 20 Oct 2019
Switching Regression Models and Causal Inference in the Presence of Discrete Latent Variables Rune Christiansen J. Peters CML 26 14 0 16 Aug 2018
Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders Patrick Forré Joris M. Mooij CML 92 56 0 09 Jul 2018
Learning Bayesian Networks from Big Data with Greedy Search: Computational Complexity and Efficient Implementation M. Scutari C. Vitolo A. Tucker 78 99 0 22 Apr 2018
Comparative Benchmarking of Causal Discovery Techniques Karamjit Singh Garima Gupta Vartika Tewari Gautam M. Shroff CML 115 13 0 18 Aug 2017
Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs Emilija Perković J. Textor M. Kalisch Marloes H. Maathuis OffRL 95 149 0 22 Jun 2016
Structure Learning in Graphical Modeling Mathias Drton Marloes H. Maathuis CML 112 253 0 07 Jun 2016
Identifiability Assumptions and Algorithm for Directed Graphical Models with Feedback G. Park Garvesh Raskutti CML 29 6 0 14 Feb 2016
Distributional Equivalence and Structure Learning for Bow-free Acyclic Path Diagrams Christopher Nowzohour Marloes H. Maathuis R. Evans Peter Buhlmann 96 22 0 07 Aug 2015
A Complete Generalized Adjustment Criterion Emilija Perković J. Textor M. Kalisch Marloes H. Maathuis OffRL CML 85 73 0 06 Jul 2015