ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2204.04644
  4. Cited By
From graphs to DAGs: a low-complexity model and a scalable algorithm

From graphs to DAGs: a low-complexity model and a scalable algorithm

10 April 2022
Shuyu Dong
Michèle Sebag
    CML
ArXiv (abs)PDFHTML

Papers citing "From graphs to DAGs: a low-complexity model and a scalable algorithm"

13 / 13 papers shown
Title
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data
Yue Cheng
Jiajun Zhang
Weiwei Xing
Xiaoyu Guo
Yue Cheng
Witold Pedrycz
CML
120
0
0
25 Oct 2024
Counterfactual Generative Networks
Counterfactual Generative Networks
Axel Sauer
Andreas Geiger
OODBDLCML
90
127
0
15 Jan 2021
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
Ignavier Ng
AmirEmad Ghassami
Kun Zhang
CML
57
190
0
17 Jun 2020
On Low Rank Directed Acyclic Graphs and Causal Structure Learning
On Low Rank Directed Acyclic Graphs and Causal Structure Learning
Zhuangyan Fang
Shengyu Zhu
Jiji Zhang
Yue Liu
Zhitang Chen
Yangbo He
CML
69
28
0
10 Jun 2020
Learning Sparse Nonparametric DAGs
Learning Sparse Nonparametric DAGs
Xun Zheng
Chen Dan
Bryon Aragam
Pradeep Ravikumar
Eric Xing
CML
165
261
0
29 Sep 2019
Invariant Risk Minimization
Invariant Risk Minimization
Martín Arjovsky
Léon Bottou
Ishaan Gulrajani
David Lopez-Paz
OOD
195
2,246
0
05 Jul 2019
DAG-GNN: DAG Structure Learning with Graph Neural Networks
DAG-GNN: DAG Structure Learning with Graph Neural Networks
Yue Yu
Jie Chen
Tian Gao
Mo Yu
BDLCMLGNN
82
490
0
22 Apr 2019
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive
  Learning
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning
Aapo Hyvarinen
Hiroaki Sasaki
Richard Turner
OODCML
97
331
0
22 May 2018
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs
Diviyan Kalainathan
Olivier Goudet
Isabelle M Guyon
David Lopez-Paz
Michèle Sebag
CML
58
95
0
13 Mar 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning
DAGs with NO TEARS: Continuous Optimization for Structure Learning
Xun Zheng
Bryon Aragam
Pradeep Ravikumar
Eric Xing
NoLaCMLOffRL
102
950
0
04 Mar 2018
Causal inference using invariant prediction: identification and
  confidence intervals
Causal inference using invariant prediction: identification and confidence intervals
J. Peters
Peter Buhlmann
N. Meinshausen
OOD
124
974
0
06 Jan 2015
CAM: Causal additive models, high-dimensional order search and penalized
  regression
CAM: Causal additive models, high-dimensional order search and penalized regression
Peter Buhlmann
J. Peters
J. Ernest
CML
129
325
0
06 Oct 2013
DirectLiNGAM: A direct method for learning a linear non-Gaussian
  structural equation model
DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model
Shohei Shimizu
Takanori Inazumi
Yasuhiro Sogawa
Aapo Hyvarinen
Yoshinobu Kawahara
Takashi Washio
P. Hoyer
K. Bollen
CML
102
511
0
13 Jan 2011
1