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Order-independent constraint-based causal structure learning

14 November 2012

Papers citing "Order-independent constraint-based causal structure learning"

50 / 187 papers shown

Title
Nonlinear Causal Discovery for Grouped Data Konstantin Göbler Tobias Windisch Mathias Drton CML 95 0 0 05 Jun 2025
Nonlinear Causal Discovery through a Sequential Edge Orientation Approach Stella Huang Qing Zhou CML 20 0 0 05 Jun 2025
Uncovering Bias Mechanisms in Observational Studies Ilker Demirel Zeshan Hussain Piersilvio De Bartolomeis D. Sontag CML 36 0 0 01 Jun 2025
RAGSynth: Synthetic Data for Robust and Faithful RAG Component Optimization Haiyang Shen Hang Yan Zhongshi Xing Mugeng Liu Yue Li Zhi Chen Yun Wang Jiuzheng Wang Yudong Han SyDa 113 0 0 16 May 2025
dcFCI: Robust Causal Discovery Under Latent Confounding, Unfaithfulness, and Mixed Data Adèle H. Ribeiro Dominik Heider CML 75 0 0 10 May 2025
Characterization and Learning of Causal Graphs from Hard Interventions Zihan Zhou Muhammad Qasim Elahi Murat Kocaoglu CML 126 0 0 02 May 2025
FairPlay: A Collaborative Approach to Mitigate Bias in Datasets for Improved AI Fairness Tina Behzad Mithilesh Singh Anthony J. Ripa Klaus Mueller 92 0 0 22 Apr 2025
Stable Structure Learning with HC-Stable and Tabu-Stable Algorithms N. K. Kitson Anthony C. Constantinou 83 0 0 02 Apr 2025
Constraint-based causal discovery with tiered background knowledge and latent variables in single or overlapping datasets Christine W. Bang Vanessa Didelez CML 158 0 0 27 Mar 2025
Heterogeneous Causal Discovery of Repeated Undesirable Health Outcomes Shishir Adhikari Guido Muscioni Mark Shapiro Plamen Petrov Elena Zheleva CML 98 0 0 14 Mar 2025
Causally Reliable Concept Bottleneck Models Giovanni De Felice Arianna Casanova Flores Francesco De Santis Silvia Santini Johannes Schneider Pietro Barbiero Alberto Termine 139 4 0 06 Mar 2025
CausalMan: A physics-based simulator for large-scale causality Nicholas Tagliapietra J. Luettin Lavdim Halilaj Moritz Willig Tim Pychynski Kristian Kersting CML 107 0 0 18 Feb 2025
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 77 0 0 15 Feb 2025
Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning Numair Sani Daniel Malinsky I. Shpitser CML 192 16 0 10 Jan 2025
Benchmarking Constraint-Based Bayesian Structure Learning Algorithms: Role of Network Topology R. Nagarajan Marco Scutari 58 0 0 02 Jan 2025
Causal Discovery on Dependent Binary Data Alex Chen Qing Zhou CML 67 0 0 31 Dec 2024
Scalable Temporal Anomaly Causality Discovery in Large Systems: Achieving Computational Efficiency with Binary Anomaly Flag Data M. Asres C. Omlin the CMS-HCAL Collaboration 119 0 0 16 Dec 2024
MEC-IP: Efficient Discovery of Markov Equivalent Classes via Integer Programming Abdelmonem Elrefaey Rong Pan 70 0 0 22 Oct 2024
Efficient Identification of Direct Causal Parents via Invariance and Minimum Error Testing Minh Le Nguyen Mert R. Sabuncu 54 1 0 19 Sep 2024
Counterfactual Fairness by Combining Factual and Counterfactual Predictions Zeyu Zhou Tianci Liu Ruqi Bai Jing Gao Murat Kocaoglu David I. Inouye 126 2 0 03 Sep 2024
A Full DAG Score-Based Algorithm for Learning Causal Bayesian Networks with Latent Confounders Christophe Gonzales Amir-Hosein Valizadeh BDL CML 50 0 0 20 Aug 2024
Causal Discovery from Time-Series Data with Short-Term Invariance-Based Convolutional Neural Networks Rujia Shen Boran Wang Chao Zhao Yi Guan Jingchi Jiang CML BDL AI4TS 82 0 0 15 Aug 2024
Visual Analysis of Multi-outcome Causal Graphs Mengjie Fan Jinlu Yu Daniel Weiskopf Nan Cao Huai-Yu Wang Liang Zhou CML 58 1 0 31 Jul 2024
An Efficient Procedure for Computing Bayesian Network Structure Learning Hongming Huang Joe Suzuki 44 0 0 24 Jul 2024
Scalable Variational Causal Discovery Unconstrained by Acyclicity Nu Hoang Bao Duong Thin Nguyen CML 90 0 0 06 Jul 2024
Spatio-Temporal Graphical Counterfactuals: An Overview Mingyu Kang Duxin Chen Ziyuan Pu Jianxi Gao Wenwu Yu CML 107 1 0 02 Jul 2024
Causal Inference with Latent Variables: Recent Advances and Future Prospectives Yaochen Zhu Yinhan He Jing Ma Mengxuan Hu Sheng Li Jundong Li CML 71 3 0 20 Jun 2024
Investigating potential causes of Sepsis with Bayesian network structure learning Bruno Petrungaro N. K. Kitson Anthony C. Constantinou CML 129 0 0 13 Jun 2024
Large Language Models for Constrained-Based Causal Discovery Kai-Hendrik Cohrs Gherardo Varando Emiliano Díaz Vasileios Sitokonstantinou Gustau Camps-Valls 110 12 0 11 Jun 2024
Causal Discovery with Fewer Conditional Independence Tests Kirankumar Shiragur Jiaqi Zhang Caroline Uhler CML 51 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
Better Simulations for Validating Causal Discovery with the DAG-Adaptation of the Onion Method Bryan Andrews Erich Kummerfeld CML 65 6 0 21 May 2024
Argumentative Causal Discovery Fabrizio Russo Anna Rapberger Francesca Toni CML 72 1 0 18 May 2024
CausalBench: A Comprehensive Benchmark for Causal Learning Capability of Large Language Models Yu Zhou Xingyu Wu Beichen Huang Jibin Wu Liang Feng Kay Chen Tan ELM CML 73 8 0 09 Apr 2024
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View Haoyue Dai Ignavier Ng Gongxu Luo Peter Spirtes P. Stojanov Kun Zhang CML 68 7 0 21 Mar 2024
Investigating the validity of structure learning algorithms in identifying risk factors for intervention in patients with diabetes Sheresh Zahoor Anthony C. Constantinou Tim M Curtis Mohammed Hasanuzzaman CML 54 0 0 21 Mar 2024
Recursive Causal Discovery Ehsan Mokhtarian Sepehr Elahi S. Akbari Negar Kiyavash CML 77 2 0 14 Mar 2024
Towards Automated Causal Discovery: a case study on 5G telecommunication data Konstantina Biza Antonios Ntroumpogiannis Sofia Triantafillou Ioannis Tsamardinos 62 0 0 22 Feb 2024
CURE: Simulation-Augmented Auto-Tuning in Robotics Md. Abir Hossen Sonam Kharade Jason M. O'Kane B. Schmerl David Garlan Pooyan Jamshidi 95 1 0 08 Feb 2024
Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach Aoqi Zuo Yiqing Li Susan Wei Biwei Huang FaML 69 6 0 19 Jan 2024
Shapley-PC: Constraint-based Causal Structure Learning with a Shapley Inspired Framework Fabrizio Russo Francesca Toni 82 0 0 18 Dec 2023
Multi-granularity Causal Structure Learning Jiaxuan Liang Jun Wang Guoxian Yu Shuyin Xia Guoyin Wang CML 17 2 0 09 Dec 2023
Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesian Network Structure Learning Ouyang Hui Cheng Chen Ke Tang 42 1 0 04 Dec 2023
Distributionally Robust Skeleton Learning of Discrete Bayesian Networks Yeshu Li Brian Ziebart OOD 75 1 0 10 Nov 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
Causal discovery using dynamically requested knowledge N. K. Kitson Anthony C. Constantinou CML 37 1 0 17 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 126 7 0 21 Sep 2023
Developing A Fair Individualized Polysocial Risk Score (iPsRS) for Identifying Increased Social Risk of Hospitalizations in Patients with Type 2 Diabetes (T2D) Yu Huang Jingchuan Guo W. Donahoo Zhengkang Fan Ying Lu Wei-Han Chen Huilin Tang Lori Bilello E. Shenkman Jiang Bian 79 1 0 05 Sep 2023
Using machine learning to understand causal relationships between urban form and travel CO2 emissions across continents Felix Wagner Florian Nachtigall Lukas Franken Nikola Milojevic-Dupont R. Pereira Nicolas Koch J. Runge Marta C. González F. Creutzig AI4CE 39 1 0 31 Aug 2023
Testing Sparsity Assumptions in Bayesian Networks Luke Duttweiler Sally W. Thurston A. Almudevar 53 0 0 12 Jul 2023