DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks

18 October 2020

Papers citing "DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks"

10 / 10 papers shown

Title
Sparse Bayesian Estimation of Parameters in Linear-Gaussian State-Space Models Benjamin Cox Victor Elvira 28 10 0 20 Jun 2023
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data Uzma Hasan Emam Hossain Md. Osman Gani CML AI4TS 17 24 0 27 Mar 2023
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 48 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 17 25 0 30 Aug 2022
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery Chris Cundy Aditya Grover Stefano Ermon CML 32 72 0 06 Dec 2021
Towards Federated Bayesian Network Structure Learning with Continuous Optimization Ignavier Ng Kun Zhang FedML 34 37 0 18 Oct 2021
DAGs with No Curl: An Efficient DAG Structure Learning Approach Yue Yu Tian Gao Naiyu Yin Q. Ji CML 17 59 0 14 Jun 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 18 296 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
Learning Sparse Nonparametric DAGs Xun Zheng Chen Dan Bryon Aragam Pradeep Ravikumar Eric P. Xing CML 101 258 0 29 Sep 2019