Learning Sparse Nonparametric DAGs

29 September 2019

Papers citing "Learning Sparse Nonparametric DAGs"

47 / 47 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
Causal Temporal Regime Structure Learning Abdellah Rahmani Pascal Frossard CML 75 2 0 20 Feb 2025
Standardizing Structural Causal Models Weronika Ormaniec Scott Sussex Lars Lorch Bernhard Schölkopf Andreas Krause CML 47 5 0 17 Jun 2024
ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs Ryan Thompson Edwin V. Bonilla Robert Kohn 31 0 0 24 May 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 34 8 0 28 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 20 1 0 29 Nov 2023
Recovering Linear Causal Models with Latent Variables via Cholesky Factorization of Covariance Matrix Yunfeng Cai Xu Li Ming Sun Ping Li CML 19 1 0 01 Nov 2023
Robustness of Algorithms for Causal Structure Learning to Hyperparameter Choice Damian Machlanski Spyridon Samothrakis Paul Clarke CML 24 1 0 27 Oct 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
$$\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
Learning DAGs from Data with Few Root Causes Panagiotis Misiakos Chris Wendler Markus Püschel CML 29 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 35 72 0 21 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 21 9 0 05 May 2023
GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network Yang Sun Yifan Xie BDL CML 21 1 0 28 Jan 2023
DAG Learning on the Permutahedron Valentina Zantedeschi Luca Franceschi Jean Kaddour Matt J. Kusner Vlad Niculae 25 11 0 27 Jan 2023
Deep Causal Learning for Robotic Intelligence Y. Li CML 17 5 0 23 Dec 2022
Directed Acyclic Graph Structure Learning from Dynamic Graphs Shaohua Fan Shuyang Zhang Xiao Wang Chuan Shi CML 31 5 0 30 Nov 2022
Towards Privacy-Aware Causal Structure Learning in Federated Setting Jianli Huang Xianjie Guo Kui Yu Fuyuan Cao Jiye Liang FedML 24 9 0 13 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 18 36 0 31 Oct 2022
Causal Structure Learning with Recommendation System Shuyuan Xu Da Xu Evren Körpeoglu Sushant Kumar Stephen D. Guo Kannan Achan Yongfeng Zhang CML 11 6 0 19 Oct 2022
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 53 78 0 16 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 22 25 0 30 Aug 2022
The tropical geometry of causal inference for extremes N. Tran CML 11 4 0 20 Jul 2022
Interactive Visual Reasoning under Uncertainty Manjie Xu Guangyuan Jiang Wei Liang Song-Chun Zhu Yixin Zhu LRM 37 5 0 18 Jun 2022
Learning to Infer Structures of Network Games Emanuele Rossi Federico Monti Yan Leng Michael M. Bronstein Xiaowen Dong 12 9 0 16 Jun 2022
Large-Scale Differentiable Causal Discovery of Factor Graphs Romain Lopez Jan-Christian Hütter J. Pritchard Aviv Regev CML AI4CE 40 40 0 15 Jun 2022
BaCaDI: Bayesian Causal Discovery with Unknown Interventions Alexander Hagele Jonas Rothfuss Lars Lorch Vignesh Ram Somnath Bernhard Schölkopf Andreas Krause CML BDL 31 19 0 03 Jun 2022
Differentiable Causal Discovery Under Latent Interventions Gonccalo R. A. Faria André F. T. Martins Mário A. T. Figueiredo BDL CML OOD 32 22 0 04 Mar 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
Learning Bayesian Networks in the Presence of Structural Side Information Ehsan Mokhtarian S. Akbari Fatemeh Jamshidi Jalal Etesami Negar Kiyavash 21 16 0 20 Dec 2021
gCastle: A Python Toolbox for Causal Discovery Keli Zhang Shengyu Zhu Marcus Kalander Ignavier Ng Junjian Ye Zhitang Chen Lujia Pan CML 22 59 0 30 Nov 2021
Towards Federated Bayesian Network Structure Learning with Continuous Optimization Ignavier Ng Kun Zhang FedML 42 37 0 18 Oct 2021
Efficient Bayesian network structure learning via local Markov boundary search Ming Gao Bryon Aragam 27 17 0 12 Oct 2021
Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families Goutham Rajendran Bohdan Kivva Ming Gao Bryon Aragam 21 17 0 10 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 28 42 0 06 Sep 2021
DAGs with No Curl: An Efficient DAG Structure Learning Approach Yue Yu Tian Gao Naiyu Yin Q. Ji CML 22 59 0 14 Jun 2021
Ordering-Based Causal Discovery with Reinforcement Learning Xiaoqiang Wang Yali Du Shengyu Zhu Liangjun Ke Zhitang Chen Jianye Hao Jun Wang CML 20 63 0 14 May 2021
Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data A. Lawrence Marcus Kaiser Rui Sampaio Maksim Sipos CML AI4TS 11 17 0 16 Apr 2021
Unsuitability of NOTEARS for Causal Graph Discovery Marcus Kaiser Maksim Sipos CML 17 65 0 12 Apr 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 23 296 0 03 Mar 2021
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To Game Alexander G. Reisach C. Seiler S. Weichwald CML 10 136 0 26 Feb 2021
Efficient and Scalable Structure Learning for Bayesian Networks: Algorithms and Applications Rong Zhu A. Pfadler Ziniu Wu Yuxing Han Xiaoke Yang Feng Ye Zhenping Qian Jingren Zhou Bin Cui 16 9 0 07 Dec 2020
DYNOTEARS: Structure Learning from Time-Series Data Roxana Pamfil Nisara Sriwattanaworachai Shaan Desai Philip Pilgerstorfer Paul Beaumont K. Georgatzis Bryon Aragam CML AI4TS BDL 17 187 0 02 Feb 2020
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 26 5,390 0 20 Dec 2018
A Spectral Series Approach to High-Dimensional Nonparametric Regression Ann B. Lee Rafael Izbicki BDL AI4TS 107 37 0 01 Feb 2016
Nonparametric sparsity and regularization Lorenzo Rosasco S. Villa S. Mosci M. Santoro A. Verri 83 102 0 13 Aug 2012