DAG-GNN: DAG Structure Learning with Graph Neural Networks

22 April 2019

Papers citing "DAG-GNN: DAG Structure Learning with Graph Neural Networks"

50 / 69 papers shown

Title
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions Juan L. Gamella Armeen Taeb C. Heinze-Deml Peter Buhlmann CML 91 7 0 13 Mar 2025
IGDA: Interactive Graph Discovery through Large Language Model Agents Alex Havrilla David Alvarez-Melis Nicolò Fusi AI4CE 45 0 0 24 Feb 2025
Causal Discovery via Bayesian Optimization Bao Duong Sunil Gupta Thin Nguyen 44 0 0 28 Jan 2025
SSL Framework for Causal Inconsistency between Structures and Representations Hang Chen Xinyu Yang Keqing Du Wenya Wang 52 2 0 03 Jan 2025
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data Yue Cheng Jiajun Zhang Weiwei Xing Xiaoyu Guo Yue Cheng Witold Pedrycz CML 32 0 0 25 Oct 2024
Causal Inference with Large Language Model: A Survey Jing Ma CML LRM 91 8 0 15 Sep 2024
Standardizing Structural Causal Models Weronika Ormaniec Scott Sussex Lars Lorch Bernhard Schölkopf Andreas Krause CML 56 5 0 17 Jun 2024
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning Ashka Shah Adela DePavia Nathaniel Hudson Ian T. Foster Rick L. Stevens CML 31 1 0 10 Jun 2024
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes Georg Manten Cecilia Casolo E. Ferrucci Søren Wengel Mogensen C. Salvi Niki Kilbertus CML BDL 44 8 0 28 Feb 2024
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders Christian Toth Christian Knoll Franz Pernkopf Robert Peharz CML 43 1 0 22 Feb 2024
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 32 1 0 29 Nov 2023
Causal Structure Representation Learning of Confounders in Latent Space for Recommendation Hangtong Xu Yuanbo Xu Yongjian Yang Fuzhen Zhuang CML 74 0 0 02 Nov 2023
Recovering Linear Causal Models with Latent Variables via Cholesky Factorization of Covariance Matrix Yunfeng Cai Xu Li Ming Sun Ping Li CML 21 1 0 01 Nov 2023
Tree Search in DAG Space with Model-based Reinforcement Learning for Causal Discovery Victor-Alexandru Darvariu Stephen Hailes Mirco Musolesi CML 39 2 0 20 Oct 2023
A Bayesian Take on Gaussian Process Networks Enrico Giudice Jack Kuipers G. Moffa GP 29 3 0 20 Jun 2023
Learning DAGs from Data with Few Root Causes Panagiotis Misiakos Chris Wendler Markus Püschel CML 40 10 0 25 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 26 9 0 05 May 2023
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data Uzma Hasan Emam Hossain Md. Osman Gani CML AI4TS 31 24 0 27 Mar 2023
Directed Acyclic Graphs With Tears Zhichao Chen Zhiqiang Ge CML 33 5 0 04 Feb 2023
On Learning Necessary and Sufficient Causal Graphs Hengrui Cai Yixin Wang Michael Jordan Rui Song CML 24 12 0 29 Jan 2023
GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network Yang Sun Yifan Xie BDL CML 31 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
Directed Acyclic Graph Structure Learning from Dynamic Graphs Shaohua Fan Shuyang Zhang Xiao Wang Chuan Shi CML 36 5 0 30 Nov 2022
Disentangled Representation Learning Xin Eric Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 32 77 0 21 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
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 31 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 11 17 0 01 Nov 2022
Causal Structural Hypothesis Testing and Data Generation Models Jeffrey Q. Jiang Omead Brandon Pooladzandi Sunay Bhat Gregory Pottie CML 34 1 0 20 Oct 2022
Causal Structure Learning with Recommendation System Shuyuan Xu Da Xu Evren Körpeoglu Sushant Kumar Stephen D. Guo Kannan Achan Yongfeng Zhang CML 16 6 0 19 Oct 2022
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 59 78 0 16 Sep 2022
CausalRCA: Causal Inference based Precise Fine-grained Root Cause Localization for Microservice Applications Ruyue Xin Peng Chen Zhiming Zhao 19 36 0 06 Sep 2022
Truncated Matrix Power Iteration for Differentiable DAG Learning Zhen Zhang Ignavier Ng Dong Gong Yuhang Liu Ehsan Abbasnejad Mingming Gong Kun Zhang Javen Qinfeng Shi 32 25 0 30 Aug 2022
The tropical geometry of causal inference for extremes N. Tran CML 16 4 0 20 Jul 2022
Structural Causal 3D Reconstruction Weiyang Liu Zhen Liu Liam Paull Adrian Weller Bernhard Schölkopf 3DV CML 24 13 0 20 Jul 2022
De-Biasing Generative Models using Counterfactual Methods Sunay Bhat Jeffrey Q. Jiang Omead Brandon Pooladzandi Gregory Pottie CML 28 7 0 04 Jul 2022
Learning to Infer Structures of Network Games Emanuele Rossi Federico Monti Yan Leng Michael M. Bronstein Xiaowen Dong 16 9 0 16 Jun 2022
Large-Scale Differentiable Causal Discovery of Factor Graphs Romain Lopez Jan-Christian Hütter J. Pritchard Aviv Regev CML AI4CE 45 40 0 15 Jun 2022
On the Generalization and Adaption Performance of Causal Models Nino Scherrer Anirudh Goyal Stefan Bauer Yoshua Bengio Nan Rosemary Ke CML OOD BDL TTA 31 8 0 09 Jun 2022
BaCaDI: Bayesian Causal Discovery with Unknown Interventions Alexander Hagele Jonas Rothfuss Lars Lorch Vignesh Ram Somnath Bernhard Schölkopf Andreas Krause CML BDL 44 19 0 03 Jun 2022
Amortized Inference for Causal Structure Learning Lars Lorch Scott Sussex Jonas Rothfuss Andreas Krause Bernhard Schölkopf CML 26 60 0 25 May 2022
uGLAD: Sparse graph recovery by optimizing deep unrolled networks H. Shrivastava Urszula Chajewska Robin Abraham Xinshi Chen 36 8 0 23 May 2022
Causal discovery for observational sciences using supervised machine learning A. H. Petersen Joseph Ramsey C. Ekstrøm Peter Spirtes CML 30 14 0 25 Feb 2022
Distributed Learning of Generalized Linear Causal Networks Qiaoling Ye Arash A. Amini Qing Zhou CML OOD AI4CE 35 16 0 23 Jan 2022
GCS: Graph-based Coordination Strategy for Multi-Agent Reinforcement Learning Jingqing Ruan Yali Du Xuantang Xiong Dengpeng Xing Xiyun Li Linghui Meng Haifeng Zhang Jun Wang Bo Xu 38 29 0 17 Jan 2022
Feature Selection for Efficient Local-to-Global Bayesian Network Structure Learning Kui Yu Zhaolong Ling Lin Liu Hao Wang Jiuyong Li 28 4 0 20 Dec 2021
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery Chris Cundy Aditya Grover Stefano Ermon CML 40 72 0 06 Dec 2021
gCastle: A Python Toolbox for Causal Discovery Keli Zhang Shengyu Zhu Marcus Kalander Ignavier Ng Junjian Ye Zhitang Chen Lujia Pan CML 24 60 0 30 Nov 2021
Towards Federated Bayesian Network Structure Learning with Continuous Optimization Ignavier Ng Kun Zhang FedML 47 38 0 18 Oct 2021
Learning Neural Causal Models with Active Interventions Nino Scherrer O. Bilaniuk Yashas Annadani Anirudh Goyal Patrick Schwab Bernhard Schölkopf Michael C. Mozer Yoshua Bengio Stefan Bauer Nan Rosemary Ke CML 40 42 0 06 Sep 2021