D'ya like DAGs? A Survey on Structure Learning and Causal Discovery

3 March 2021

Papers citing "D'ya like DAGs? A Survey on Structure Learning and Causal Discovery"

50 / 165 papers shown

Title
Boosting Causal Additive Models Maximilian Kertel Nadja Klein 35 0 0 12 Jan 2024
Dagma-DCE: Interpretable, Non-Parametric Differentiable Causal Discovery Daniel Waxman Kurt Butler P. Djuric 28 3 0 05 Jan 2024
Is Knowledge All Large Language Models Needed for Causal Reasoning? Hengrui Cai Shengjie Liu Rui Song LRM ELM 20 10 0 30 Dec 2023
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 28 2 0 19 Dec 2023
Shapley-PC: Constraint-based Causal Structure Learning with a Shapley Inspired Framework Fabrizio Russo Francesca Toni 17 0 0 18 Dec 2023
Entropy Causal Graphs for Multivariate Time Series Anomaly Detection F. Febrinanto Kristen Moore Chandra Thapa Mujie Liu Vidya Saikrishna Jiangang Ma Feng Xia CML 23 2 0 15 Dec 2023
Towards Human-like Perception: Learning Structural Causal Model in Heterogeneous Graph Tianqianjin Lin Kaisong Song Zhuoren Jiang Yangyang Kang Weikang Yuan Xurui Li Changlong Sun Cui Huang Xiaozhong Liu 30 6 0 10 Dec 2023
Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge Xiaoge Zhang Xiao-Lin Wang Fenglei Fan Yiu-ming Cheung Indranil Bose 20 1 0 29 Nov 2023
Equilibrium in the Computing Continuum through Active Inference Boris Sedlak Víctor Casamayor Pujol Praveen Kumar Donta Schahram Dustdar 18 16 0 28 Nov 2023
Structural Discovery with Partial Ordering Information for Time-Dependent Data with Convergence Guarantees Jiahe Lin Huitian Lei G. Michailidis 14 1 0 26 Nov 2023
Causal Fairness-Guided Dataset Reweighting using Neural Networks Xuan Zhao Klaus Broelemann Salvatore Ruggieri Gjergji Kasneci 11 1 0 17 Nov 2023
A Review and Roadmap of Deep Causal Model from Different Causal Structures and Representations Hang Chen Keqing Du Chenguang Li Xinyu Yang 39 2 0 02 Nov 2023
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling Aneesh Komanduri Xintao Wu Yongkai Wu Feng Chen CML OOD 31 7 0 17 Oct 2023
CoLiDE: Concomitant Linear DAG Estimation S. S. Saboksayr Gonzalo Mateos Mariano Tepper CML 30 4 0 04 Oct 2023
CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery Yuxiao Cheng Ziqian Wang Tingxiong Xiao Qin Zhong J. Suo Kunlun He AI4TS CML 30 11 0 03 Oct 2023
Constraint-Free Structure Learning with Smooth Acyclic Orientations Riccardo Massidda Francesco Landolfi Martina Cinquini Davide Bacciu 23 6 0 15 Sep 2023
RDGSL: Dynamic Graph Representation Learning with Structure Learning Siwei Zhang Yun Xiong Yao Zhang Yiheng Sun Xiangshan Chen Yizhu Jiao Yangyong Zhu NoLa 29 11 0 05 Sep 2023
Through the Lens of Core Competency: Survey on Evaluation of Large Language Models Ziyu Zhuang Qiguang Chen Longxuan Ma Mingda Li Yi Han Yushan Qian Haopeng Bai Zixian Feng Weinan Zhang Ting Liu ELM 24 9 0 15 Aug 2023
Order-based Structure Learning with Normalizing Flows Hamidreza Kamkari Vahid Balazadeh Meresht Vahid Zehtab Rahul G. Krishnan CML 26 1 0 14 Aug 2023
Learning nonparametric DAGs with incremental information via high-order HSIC Yafei Wang Jianguo Liu CML 19 0 0 11 Aug 2023
SLEM: Machine Learning for Path Modeling and Causal Inference with Super Learner Equation Modeling M. Vowels CML 14 1 0 08 Aug 2023
CausalOps -- Towards an Industrial Lifecycle for Causal Probabilistic Graphical Models R. Maier A. Schlattl Thomas Guess J. Mottok AI4CE 26 1 0 02 Aug 2023
ICCPS: Impact discovery using causal inference for cyber attacks in CPSs R. Maiti Sridhar Adepu Emil C. Lupu 14 1 0 26 Jul 2023
Linking vision and motion for self-supervised object-centric perception Kaylene C. Stocking Zak Murez Vijay Badrinarayanan Jamie Shotton Alex Kendall Claire Tomlin Christopher P. Burgess OCL 28 0 0 14 Jul 2023
Identifiability Guarantees for Causal Disentanglement from Soft Interventions Jiaqi Zhang C. Squires Kristjan Greenewald Akash Srivastava Karthikeyan Shanmugam Caroline Uhler CML 46 53 0 12 Jul 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris C. Emezue Alexandre Drouin T. Deleu Stefan Bauer Yoshua Bengio CML 27 2 0 11 Jul 2023
Causal Reinforcement Learning: A Survey Zhi-Hong Deng Jing Jiang Guodong Long Chen Zhang CML LRM 45 13 0 04 Jul 2023
$$\texttt{causalAssembly}$: Generating Realistic Production Data for Benchmarking Causal Discovery$ $\texttt{causalAssembly}$ : Generating Realistic Production Data for Benchmarking Causal Discovery Konstantin Göbler Tobias Windisch Mathias Drton T. Pychynski Steffen Sonntag Martin Roth CML 67 9 0 19 Jun 2023
Dynamic Causal Graph Convolutional Network for Traffic Prediction Junpeng Lin Ziyue Li Zhishuai Li Lei Bai Rui Zhao Chen Zhang GNN AI4TS 10 17 0 12 Jun 2023
Discovering Dynamic Causal Space for DAG Structure Learning F. Liu Wenchang Ma An Zhang Xiang Wang Yueqi Duan Tat-Seng Chua OOD CML 11 2 0 05 Jun 2023
Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation Wanpeng Zhang Yilin Li Boyu Yang Zongqing Lu CML 10 0 0 05 Jun 2023
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms Aneesh Komanduri Yongkai Wu Feng Chen Xintao Wu CML OOD 13 9 0 02 Jun 2023
Learning DAGs from Data with Few Root Causes Panagiotis Misiakos Chris Wendler Markus Püschel CML 29 10 0 25 May 2023
CUTS+: High-dimensional Causal Discovery from Irregular Time-series Yuxiao Cheng Lianglong Li Tingxiong Xiao Zongren Li Qionghai Dai J. Suo K. He CML BDL AI4TS 21 21 0 10 May 2023
Towards Causal Representation Learning and Deconfounding from Indefinite Data Hang Chen Xinyu Yang Qing Yang OOD CML 19 0 0 04 May 2023
Causal Discovery and Optimal Experimental Design for Genome-Scale Biological Network Recovery Ashka Shah A. Ramanathan Valérie Hayot-Sasson Rick L. Stevens CML 14 1 0 06 Apr 2023
Structure Learning with Continuous Optimization: A Sober Look and Beyond Ignavier Ng Biwei Huang Kun Zhang CML 21 21 0 04 Apr 2023
A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models Alexander G. Reisach Myriam Tami C. Seiler Antoine Chambaz S. Weichwald CML 28 19 0 31 Mar 2023
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data Uzma Hasan Emam Hossain Md. Osman Gani CML AI4TS 26 24 0 27 Mar 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 20 1 0 10 Mar 2023
Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting An Zhang Fang Liu Wenchang Ma Zhibo Cai Xiang Wang Tat-Seng Chua CML 24 5 0 06 Mar 2023
Achieving Counterfactual Fairness for Anomaly Detection Xiao Han Lu Zhang Yongkai Wu Shuhan Yuan 6 6 0 04 Mar 2023
CUTS: Neural Causal Discovery from Irregular Time-Series Data Yuxiao Cheng Runzhao Yang Tingxiong Xiao Zongren Li J. Suo K. He Qionghai Dai OOD BDL AI4TS CML 14 24 0 15 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality Gael Gendron Michael Witbrock Gillian Dobbie OOD AI4CE CML 14 12 0 01 Feb 2023
On Learning Necessary and Sufficient Causal Graphs Hengrui Cai Yixin Wang Michael Jordan Rui Song CML 16 12 0 29 Jan 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Biwei Huang Xiwei Xu Chen Wang Liming Zhu Lina Yao Kun Zhang AI4CE 47 11 0 29 Jan 2023
Causal Structural Learning from Time Series: A Convex Optimization Approach S. Wei Yao Xie CML 27 2 0 26 Jan 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 17 1 0 16 Jan 2023
On the causality-preservation capabilities of generative modelling Yves-Cédric Bauwelinckx Jan Dhaene Tim Verdonck Milan van den Heuvel CML AI4CE 30 0 0 03 Jan 2023