DAGs with NO TEARS: Continuous Optimization for Structure Learning

4 March 2018

Papers citing "DAGs with NO TEARS: Continuous Optimization for Structure Learning"

50 / 191 papers shown

Title
Tree Search in DAG Space with Model-based Reinforcement Learning for Causal Discovery Victor-Alexandru Darvariu Stephen Hailes Mirco Musolesi CML 46 2 0 20 Oct 2023
Discovering Mixtures of Structural Causal Models from Time Series Data Sumanth Varambally Yi Ma Rose Yu 22 4 0 10 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
Differentiable Bayesian Structure Learning with Acyclicity Assurance Quang-Duy Tran Phuoc Nguyen Bao Duong Thin Nguyen 32 2 0 04 Sep 2023
The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data Mathieu Chevalley Jacob A. Sackett-Sanders Yusuf Roohani Pascal Notin A. Bakulin ... Achille Nazaret Markus Püschel Chris Wendler Arash Mehrjou Patrick Schwab CML 36 10 0 29 Aug 2023
Order-based Structure Learning with Normalizing Flows Hamidreza Kamkari Vahid Balazadeh Meresht Vahid Zehtab Rahul G. Krishnan CML 35 1 0 14 Aug 2023
Learning nonparametric DAGs with incremental information via high-order HSIC Yafei Wang Jianguo Liu CML 27 0 0 11 Aug 2023
Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space Models Benjamin Cox Victor Elvira 41 10 0 20 Jun 2023
A Bayesian Take on Gaussian Process Networks Enrico Giudice Jack Kuipers G. Moffa GP 29 3 0 20 Jun 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 73 10 0 19 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 23 56 0 01 Jun 2023
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network T. Deleu Mizu Nishikawa-Toomey Jithendaraa Subramanian Nikolay Malkin Laurent Charlin Yoshua Bengio BDL 32 43 0 30 May 2023
Learning DAGs from Data with Few Root Causes Panagiotis Misiakos Chris Wendler Markus Püschel CML 44 10 0 25 May 2023
Discovering Causal Relations and Equations from Data Gustau Camps-Valls Andreas Gerhardus Urmi Ninad Gherardo Varando Georg Martius E. Balaguer-Ballester Ricardo Vinuesa Emiliano Díaz L. Zanna Jakob Runge PINN AI4Cl AI4CE CML 44 73 0 21 May 2023
A Survey on Causal Discovery: Theory and Practice Alessio Zanga Fabio Stella CML 39 38 0 17 May 2023
Open problems in causal structure learning: A case study of COVID-19 in the UK Anthony C. Constantinou N. K. Kitson Yang Liu Kiattikun Chobtham Arian Hashemzadeh Praharsh Nanavati R. Mbuvha Bruno Petrungaro CML 32 9 0 05 May 2023
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach Christo Kurisummoottil Thomas Walid Saad Yong Xiao 37 20 0 25 Apr 2023
On Learning Time Series Summary DAGs: A Frequency Domain Approach Aramayis Dallakyan CML AI4TS 30 3 0 17 Apr 2023
DiscoGen: Learning to Discover Gene Regulatory Networks Nan Rosemary Ke Sara-Jane Dunn J. Bornschein Silvia Chiappa Mélanie Rey ... David Barrett M. Botvinick Anirudh Goyal Michael C. Mozer Danilo Jimenez Rezende BDL CML 19 4 0 12 Apr 2023
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise Francesco Montagna Nicoletta Noceti Lorenzo Rosasco Kun Zhang Francesco Locatello CML 15 27 0 06 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 36 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 35 24 0 27 Mar 2023
Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting An Zhang Fang Liu Wenchang Ma Zhibo Cai Xiang Wang Tat-Seng Chua CML 40 5 0 06 Mar 2023
MetaPhysiCa: OOD Robustness in Physics-informed Machine Learning S Chandra Mouli M. A. Alam Bruno Ribeiro OOD 29 4 0 06 Mar 2023
Q-Cogni: An Integrated Causal Reinforcement Learning Framework C. Cunha Wei Liu T. French Ajmal Mian 26 1 0 26 Feb 2023
Brain Effective Connectome based on fMRI and DTI Data: Bayesian Causal Learning and Assessment Abdolmahdi Bagheri Mahdi Dehshiri Yamin Bagheri Alireza Akhondi-Asl Babak N. Araabi 19 4 0 10 Feb 2023
CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data Muhammad Hasan Ferdous Uzma Hasan Md. Osman Gani CML 42 3 0 07 Feb 2023
Directed Acyclic Graphs With Tears Zhichao Chen Zhiqiang Ge CML 33 5 0 04 Feb 2023
Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization Dongjie Wang Zhengzhang Chen Jingchao Ni Liang Tong Zheng Wang Yanjie Fu Haifeng Chen AI4CE 11 17 0 03 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality Gaël Gendron Michael Witbrock Gillian Dobbie OOD AI4CE CML 39 13 0 01 Feb 2023
On Learning Necessary and Sufficient Causal Graphs Hengrui Cai Yixin Wang Michael Jordan Rui Song CML 34 12 0 29 Jan 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Erdun Gao Xiwei Xu Chen Wang Liming Zhu Lina Yao Kun Zhang AI4CE 57 11 0 29 Jan 2023
GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network Yang Sun Yifan Xie BDL CML 34 1 0 28 Jan 2023
DAG Learning on the Permutahedron Valentina Zantedeschi Luca Franceschi Jean Kaddour Matt J. Kusner Vlad Niculae 27 11 0 27 Jan 2023
Causal Structural Learning from Time Series: A Convex Optimization Approach S. Wei Yao Xie CML 32 2 0 26 Jan 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 30 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 38 0 0 03 Jan 2023
Deep Learning of Causal Structures in High Dimensions Kai Lagemann C. Lagemann B. Taschler S. Mukherjee CML BDL AI4CE 30 29 0 09 Dec 2022
Directed Acyclic Graph Structure Learning from Dynamic Graphs Shaohua Fan Shuyang Zhang Xiao Wang Chuan Shi CML 39 5 0 30 Nov 2022
Estimation of a Causal Directed Acyclic Graph Process using Non-Gaussianity A. Einizade S. H. Sardouie CML 34 0 0 24 Nov 2022
$Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery$ Trust Your $\nabla$ : Gradient-based Intervention Targeting for Causal Discovery Mateusz Olko Michal Zajac A. Nowak Nino Scherrer Yashas Annadani Stefan Bauer Lukasz Kucinski Piotr Milos CML 41 2 0 24 Nov 2022
Realization of Causal Representation Learning to Adjust Confounding Bias in Latent Space Jia Li Xiang Li X. Jia M. Steinbach Vipin Kumar CML OOD AI4CE 24 0 0 15 Nov 2022
Towards Privacy-Aware Causal Structure Learning in Federated Setting Jianli Huang Xianjie Guo Kui Yu Fuyuan Cao Jiye Liang FedML 29 9 0 13 Nov 2022
Improving the Efficiency of the PC Algorithm by Using Model-Based Conditional Independence Tests Erica Cai A. Mcgregor David D. Jensen CML 29 1 0 12 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 36 11 0 07 Nov 2022
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks Yue Yu Xuan Kan Hejie Cui Ran Xu Yu Zheng ... Kun Zhang Razieh Nabi Ying Guo Chaogang Zhang Carl Yang 13 17 0 01 Nov 2022
CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data Mathieu Chevalley Yusuf Roohani Arash Mehrjou J. Leskovec Patrick Schwab CML 26 37 0 31 Oct 2022
Learning Causal Graphs in Manufacturing Domains using Structural Equation Models Maximilian Kertel Stefan Harmeling Markus Pauly CML 32 4 0 26 Oct 2022
Learning Latent Structural Causal Models Jithendaraa Subramanian Yashas Annadani Ivaxi Sheth Nan Rosemary Ke T. Deleu Stefan Bauer Derek Nowrouzezahrai Samira Ebrahimi Kahou CML 30 7 0 24 Oct 2022
Causal Structural Hypothesis Testing and Data Generation Models Jeffrey Q. Jiang Omead Brandon Pooladzandi Sunay Bhat Gregory Pottie CML 40 1 0 20 Oct 2022