Learning linear structural equation models in polynomial time and sample complexity

15 July 2017

Papers citing "Learning linear structural equation models in polynomial time and sample complexity"

17 / 17 papers shown

Title
Score matching through the roof: linear, nonlinear, and latent variables causal discovery Francesco Montagna P. M. Faller Patrick Bloebaum Elke Kirschbaum Francesco Locatello CML 81 0 0 26 Jul 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
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
Order-based Structure Learning with Normalizing Flows Hamidreza Kamkari Vahid Balazadeh Meresht Vahid Zehtab Rahul G. Krishnan CML 26 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
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 53 78 0 16 Sep 2022
Order-based Structure Learning without Score Equivalence Hyunwoong Chang James Cai Quan Zhou CML OffRL 19 3 0 10 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
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
Confidence in Causal Discovery with Linear Causal Models David Strieder Tobias Freidling Stefan Haffner Mathias Drton CML 11 11 0 10 Jun 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
On Causal Discovery with Equal Variance Assumption Wenyu Chen Mathias Drton Y Samuel Wang CML 14 84 0 09 Jul 2018
Learning Polytrees S. Dasgupta TPM 62 129 0 23 Jan 2013