v1v2 (latest)

Gradient-Based Neural DAG Learning

5 June 2019

Papers citing "Gradient-Based Neural DAG Learning"

50 / 188 papers shown

Title
Reinforcement Causal Structure Learning on Order Graph Dezhi Yang Guoxian Yu Jun Wang Zhe Wu Maozu Guo BDL CML 100 16 0 22 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 109 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 68 9 0 13 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 119 11 0 07 Nov 2022
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes Mizu Nishikawa-Toomey T. Deleu Jithendaraa Subramanian Yoshua Bengio Laurent Charlin BDL CML 111 29 0 04 Nov 2022
Learning Discrete Directed Acyclic Graphs via Backpropagation A. Wren Pasquale Minervini Luca Franceschi Valentina Zantedeschi 58 2 0 27 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 94 7 0 24 Oct 2022
Causal Structure Learning with Recommendation System Shuyuan Xu Da Xu Evren Körpeoglu Sushant Kumar Stephen D. Guo Kannan Achan Yongfeng Zhang CML 77 6 0 19 Oct 2022
GFlowCausal: Generative Flow Networks for Causal Discovery Wenqian Li Yinchuan Li Shengyu Zhu Yunfeng Shao Jianye Hao Yan Pang BDL CML 65 12 0 15 Oct 2022
Causality-driven Hierarchical Structure Discovery for Reinforcement Learning Shaohui Peng Xin Hu Rui Zhang Ke Tang Jiaming Guo ... Xishan Zhang Zidong Du Ling Li Qi Guo Yunji Chen 76 23 0 13 Oct 2022
Diffusion Models for Causal Discovery via Topological Ordering Pedro Sanchez Xiao Liu Alison Q. OÑeil Sotirios A. Tsaftaris DiffM 149 49 0 12 Oct 2022
Neural Graphical Models H. Shrivastava Urszula Chajewska 101 11 0 02 Oct 2022
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 115 84 0 16 Sep 2022
On the Sparse DAG Structure Learning Based on Adaptive Lasso Danru Xu Erdun Gao Wei Huang Menghan Wang Andy Song Biwei Huang CML 85 4 0 07 Sep 2022
Truncated Matrix Power Iteration for Differentiable DAG Learning Zhen Zhang Ignavier Ng Dong Gong Yuhang Liu Ehsan Abbasnejad Biwei Huang Kun Zhang Javen Qinfeng Shi 75 25 0 30 Aug 2022
Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables Ehsan Mokhtarian M. Khorasani Jalal Etesami Negar Kiyavash CML 80 7 0 14 Aug 2022
DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction Yanke Li Hatt Tobias Ioana Bica M. Schaar CML 78 0 0 02 Aug 2022
Towards Intercultural Affect Recognition: Audio-Visual Affect Recognition in the Wild Across Six Cultures Leena Mathur R. Adolphs Maja J. Matarić CVBM 88 1 0 31 Jul 2022
The tropical geometry of causal inference for extremes N. Tran CML 52 4 0 20 Jul 2022
Multiscale Causal Structure Learning Gabriele DÁcunto P. Lorenzo Sergio Barbarossa 98 7 0 16 Jul 2022
Reframed GES with a Neural Conditional Dependence Measure Xinwei Shen Shengyu Zhu Jiji Zhang Shoubo Hu Zhitang Chen CML 29 3 0 17 Jun 2022
Large-Scale Differentiable Causal Discovery of Factor Graphs Romain Lopez Jan-Christian Hütter J. Pritchard Aviv Regev CML AI4CE 87 43 0 15 Jun 2022
Invariant Structure Learning for Better Generalization and Causal Explainability Yunhao Ge Sercan O. Arik Jinsung Yoon Ao Xu Laurent Itti Tomas Pfister OOD CML 49 2 0 13 Jun 2022
Differentiable and Transportable Structure Learning Jeroen Berrevoets Nabeel Seedat F. Imrie M. Schaar 87 2 0 13 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 80 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 119 22 0 03 Jun 2022
Causality Learning With Wasserstein Generative Adversarial Networks H. Petkov Colin Hanley Feng Dong CML GAN OOD 25 0 0 03 Jun 2022
Causal Structure Learning: a Combinatorial Perspective C. Squires Caroline Uhler CML 120 47 0 02 Jun 2022
Differentiable Invariant Causal Discovery Yu Wang An Zhang Xiang Wang Yancheng Yuan Xiangnan He Tat-Seng Chua OOD CML 135 2 0 31 May 2022
MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models Erdun Gao Ignavier Ng Biwei Huang Li Shen Wei Huang Tongliang Liu Kun Zhang H. Bondell CML 139 23 0 27 May 2022
Amortized Inference for Causal Structure Learning Lars Lorch Scott Sussex Jonas Rothfuss Andreas Krause Bernhard Schölkopf CML 116 65 0 25 May 2022
Improving Multi-Task Generalization via Regularizing Spurious Correlation Ziniu Hu Zhe Zhao Xinyang Yi Tiansheng Yao Lichan Hong Yizhou Sun Ed H. Chi OOD LRM 142 30 0 19 May 2022
DAG-WGAN: Causal Structure Learning With Wasserstein Generative Adversarial Networks H. Petkov Colin Hanley Feng Dong GAN OOD CML 65 6 0 01 Apr 2022
Differentiable DAG Sampling Bertrand Charpentier Simon Kibler Stephan Günnemann 100 42 0 16 Mar 2022
Score matching enables causal discovery of nonlinear additive noise models Paul Rolland Volkan Cevher Matthäus Kleindessner Chris Russel Bernhard Schölkopf Dominik Janzing Francesco Locatello CML 99 90 0 08 Mar 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
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 89 30 0 17 Jan 2022
FedDAG: Federated DAG Structure Learning Erdun Gao Junjia Chen Li Shen Tongliang Liu Biwei Huang H. Bondell FedML 87 17 0 07 Dec 2021
gCastle: A Python Toolbox for Causal Discovery Keli Zhang Shengyu Zhu Marcus Kalander Ignavier Ng Junjian Ye Zhitang Chen Lujia Pan CML 127 61 0 30 Nov 2021
Multi-task Learning of Order-Consistent Causal Graphs Xinshi Chen Haoran Sun Caleb N. Ellington Eric Xing Le Song CML 92 15 0 03 Nov 2021
Towards Federated Bayesian Network Structure Learning with Continuous Optimization Ignavier Ng Kun Zhang FedML 91 38 0 18 Oct 2021
Simultaneous Missing Value Imputation and Structure Learning with Groups Pablo Morales-Álvarez Wenbo Gong A. Lamb Simon Woodhead Simon L. Peyton Jones Nick Pawlowski Miltiadis Allamanis Cheng Zhang 138 18 0 15 Oct 2021
Scalable Causal Structure Learning: Scoping Review of Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine Pulakesh Upadhyaya Kai Zhang Can Li Xiaoqian Jiang Yejin Kim CML 74 9 0 15 Oct 2021
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge Xiangyuan Sun Oliver Schulte Guiliang Liu Pascal Poupart CML BDL 105 22 0 09 Sep 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 123 44 0 06 Sep 2021
A Stochastic Variance-Reduced Coordinate Descent Algorithm for Learning Sparse Bayesian Network from Discrete High-Dimensional Data Nazanin Shajoonnezhad Amin Nikanjam 45 3 0 21 Aug 2021
Efficient Neural Causal Discovery without Acyclicity Constraints Phillip Lippe Taco S. Cohen E. Gavves CML 102 72 0 22 Jul 2021
Beyond Predictions in Neural ODEs: Identification and Interventions H. Aliee Fabian J. Theis Niki Kilbertus CML 118 25 0 23 Jun 2021
Identifiability of AMP chain graph models Yuhao Wang Arnab Bhattacharyya CML 22 0 0 17 Jun 2021
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures Yashas Annadani Jonas Rothfuss Alexandre Lacoste Nino Scherrer Anirudh Goyal Yoshua Bengio Stefan Bauer BDL CML 84 48 0 14 Jun 2021