Identifiability of Gaussian structural equation models with equal error variances

11 May 2012

Papers citing "Identifiability of Gaussian structural equation models with equal error variances"

48 / 48 papers shown

Title
Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery Rebecca Herman Jonas Wahl Urmi Ninad Jakob Runge 47 0 0 21 Mar 2025
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions Juan L. Gamella Armeen Taeb C. Heinze-Deml Peter Buhlmann CML 88 7 0 13 Mar 2025
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning Albert Wilcox Mohamed Ghanem Masoud Moghani Pierre Barroso Benjamin Joffe Animesh Garg 50 0 0 06 Mar 2025
Causal Temporal Regime Structure Learning Abdellah Rahmani Pascal Frossard CML 75 2 0 20 Feb 2025
ExDAG: Exact learning of DAGs Pavel Rytír Ales Wodecki Jakub Marecek CML 38 1 0 21 Jun 2024
Standardizing Structural Causal Models Weronika Ormaniec Scott Sussex Lars Lorch Bernhard Schölkopf Andreas Krause CML 44 5 0 17 Jun 2024
Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models Tong Xu Armeen Taeb Simge Kuccukyavuz Ali Shojaie CML 36 1 0 19 Apr 2024
Optimal estimation of Gaussian (poly)trees Yuhao Wang Ming Gao Wai Ming Tai Bryon Aragam Arnab Bhattacharyya TPM 16 1 0 09 Feb 2024
Bayesian Approach to Linear Bayesian Networks Seyong Hwang Kyoungjae Lee Sunmin Oh Gunwoong Park 24 0 0 27 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
Learning bounded-degree polytrees with known skeleton Davin Choo Joy Qiping Yang Arnab Bhattacharyya C. Canonne 18 2 0 10 Oct 2023
Discovering Mixtures of Structural Causal Models from Time Series Data Sumanth Varambally Yi-An Ma Rose Yu 20 4 0 10 Oct 2023
Order-based Structure Learning with Normalizing Flows Hamidreza Kamkari Vahid Balazadeh Meresht Vahid Zehtab Rahul G. Krishnan CML 23 1 0 14 Aug 2023
Identifiability of Homoscedastic Linear Structural Equation Models using Algebraic Matroids Mathias Drton Benjamin Hollering June Wu 14 1 0 03 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 62 9 0 19 Jun 2023
Passive learning of active causal strategies in agents and language models Andrew Kyle Lampinen Stephanie C. Y. Chan Ishita Dasgupta A. Nam Jane X. Wang 27 15 0 25 May 2023
Learning DAGs from Data with Few Root Causes Panagiotis Misiakos Chris Wendler Markus Püschel CML 27 10 0 25 May 2023
Identifiability of latent-variable and structural-equation models: from linear to nonlinear Aapo Hyvarinen Ilyes Khemakhem R. Monti CML 25 41 0 06 Feb 2023
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 19 25 0 30 Aug 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
Counterfactual Fairness with Partially Known Causal Graph Aoqi Zuo Susan Wei Tongliang Liu Bo Han Kun Zhang Mingming Gong OOD FaML 19 19 0 27 May 2022
Amortized Inference for Causal Structure Learning Lars Lorch Scott Sussex Jonas Rothfuss Andreas Krause Bernhard Schölkopf CML 15 60 0 25 May 2022
Ancestor regression in linear structural equation models Christoph Schultheiss Peter Buhlmann CML 9 5 0 18 May 2022
Order-based Structure Learning without Score Equivalence Hyunwoong Chang James Cai Quan Zhou CML OffRL 16 3 0 10 Feb 2022
Correcting Confounding via Random Selection of Background Variables You-Lin Chen Lenon Minorics Dominik Janzing CML 14 4 0 04 Feb 2022
Optimal estimation of Gaussian DAG models Ming Gao W. Tai Bryon Aragam 27 9 0 25 Jan 2022
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery Chris Cundy Aditya Grover Stefano Ermon CML 37 72 0 06 Dec 2021
A Fast Non-parametric Approach for Local Causal Structure Learning Mona Azadkia Armeen Taeb Peter Buhlmann CML 19 3 0 29 Nov 2021
Efficient Learning of Quadratic Variance Function Directed Acyclic Graphs via Topological Layers Wei Zhou Xin He Wei Zhong Junhui Wang CML 25 4 0 01 Nov 2021
Towards Federated Bayesian Network Structure Learning with Continuous Optimization Ignavier Ng Kun Zhang FedML 39 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
Optimization-based Causal Estimation from Heterogenous Environments Mingzhang Yin Yixin Wang David M. Blei OOD 79 17 0 24 Sep 2021
Confidence in Causal Discovery with Linear Causal Models David Strieder Tobias Freidling Stefan Haffner Mathias Drton CML 11 11 0 10 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
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
Causal Inference from Slowly Varying Nonstationary Processes Kang Du Yu Xiang 21 6 0 23 Dec 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Amir-Hossein Karimi Julius von Kügelgen Bernhard Schölkopf Isabel Valera CML 25 178 0 11 Jun 2020
Differential Network Analysis: A Statistical Perspective Ali Shojaie 33 48 0 09 Mar 2020
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values S. Weichwald M. E. Jakobsen Phillip B. Mogensen Lasse Petersen Nikolaj Thams Gherardo Varando CML AI4TS 11 25 0 21 Feb 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
On Causal Discovery with Equal Variance Assumption Wenyu Chen Mathias Drton Y Samuel Wang CML 14 84 0 09 Jul 2018
Learning linear structural equation models in polynomial time and sample complexity Asish Ghoshal Jean Honorio CML 23 83 0 15 Jul 2017
Learning Quadratic Variance Function (QVF) DAG models via OverDispersion Scoring (ODS) G. Park Garvesh Raskutti CML 16 45 0 28 Apr 2017
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity Asish Ghoshal Jean Honorio CML TPM 29 55 0 03 Mar 2017
Learning Directed Acyclic Graphs with Penalized Neighbourhood Regression Bryon Aragam Arash A. Amini Qing Zhou CML 11 42 0 29 Nov 2015
A Transformational Characterization of Equivalent Bayesian Network Structures D. M. Chickering 151 416 0 20 Feb 2013