High-dimensional learning of linear causal networks via inverse covariance estimation

14 November 2013

Papers citing "High-dimensional learning of linear causal networks via inverse covariance estimation"

27 / 27 papers shown

Title
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 69 9 0 17 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
Optimal estimation of Gaussian (poly)trees Yuhao Wang Ming Gao Wai Ming Tai Bryon Aragam Arnab Bhattacharyya TPM 16 1 0 09 Feb 2024
Sample, estimate, aggregate: A recipe for causal discovery foundation models Menghua Wu Yujia Bao Regina Barzilay Tommi Jaakkola CML 41 7 0 02 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
Bayesian Approach to Linear Bayesian Networks Seyong Hwang Kyoungjae Lee Sunmin Oh Gunwoong Park 21 0 0 27 Nov 2023
Identifiability of Homoscedastic Linear Structural Equation Models using Algebraic Matroids Mathias Drton Benjamin Hollering June Wu 14 1 0 03 Aug 2023
Testing Sparsity Assumptions in Bayesian Networks Luke Duttweiler Sally W. Thurston A. Almudevar 16 0 0 12 Jul 2023
Learning DAGs from Data with Few Root Causes Panagiotis Misiakos Chris Wendler Markus Püschel CML 27 10 0 25 May 2023
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks Yujia Zheng Ignavier Ng Yewen Fan Kun Zhang 9 4 0 19 May 2023
Causal Structural Learning from Time Series: A Convex Optimization Approach S. Wei Yao Xie CML 24 2 0 26 Jan 2023
Directed Acyclic Graph Structure Learning from Dynamic Graphs Shaohua Fan Shuyang Zhang Xiao Wang Chuan Shi CML 31 5 0 30 Nov 2022
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 50 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
Optimal estimation of Gaussian DAG models Ming Gao W. Tai Bryon Aragam 25 9 0 25 Jan 2022
A Fast Non-parametric Approach for Local Causal Structure Learning Mona Azadkia Armeen Taeb Peter Buhlmann CML 19 3 0 29 Nov 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
Unsuitability of NOTEARS for Causal Graph Discovery Marcus Kaiser Maksim Sipos CML 17 65 0 12 Apr 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
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
Identifying Best Interventions through Online Importance Sampling Rajat Sen Karthikeyan Shanmugam A. Dimakis Sanjay Shakkottai 10 72 0 10 Jan 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