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Consistency Guarantees for Greedy Permutation-Based Causal Inference
  Algorithms
v1v2v3v4 (latest)

Consistency Guarantees for Greedy Permutation-Based Causal Inference Algorithms

12 February 2017
Liam Solus
Yuhao Wang
Caroline Uhler
    CML
ArXiv (abs)PDFHTML

Papers citing "Consistency Guarantees for Greedy Permutation-Based Causal Inference Algorithms"

50 / 52 papers shown
Title
Causal Discovery and Counterfactual Reasoning to Optimize Persuasive Dialogue Policies
Causal Discovery and Counterfactual Reasoning to Optimize Persuasive Dialogue Policies
Donghuo Zeng
Roberto Legaspi
Yuewen Sun
Xinshuai Dong
Kazushi Ikeda
Peter Spirtes
Kun Zhang
CML
102
1
0
19 Mar 2025
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Juan L. Gamella
Armeen Taeb
C. Heinze-Deml
Peter Buhlmann
CML
187
8
0
13 Mar 2025
When Selection Meets Intervention: Additional Complexities in Causal Discovery
Haoyue Dai
Ignavier Ng
Jianle Sun
Zeyu Tang
Gongxu Luo
Xinshuai Dong
Peter Spirtes
Kun Zhang
CML
116
0
0
10 Mar 2025
QWO: Speeding Up Permutation-Based Causal Discovery in LiGAMs
QWO: Speeding Up Permutation-Based Causal Discovery in LiGAMs
Mohammad Shahverdikondori
Ehsan Mokhtarian
Negar Kiyavash
CML
54
0
0
30 Oct 2024
An Asymptotically Optimal Coordinate Descent Algorithm for Learning
  Bayesian Networks from Gaussian Models
An Asymptotically Optimal Coordinate Descent Algorithm for Learning Bayesian Networks from Gaussian Models
Tong Xu
Simge Küçükyavuz
Ali Shojaie
Armeen Taeb
91
0
0
21 Aug 2024
Simulation-based Benchmarking for Causal Structure Learning in Gene
  Perturbation Experiments
Simulation-based Benchmarking for Causal Structure Learning in Gene Perturbation Experiments
Luka Kovacevic
Izzy Newsham
Sach Mukherjee
John Whittaker
CML
52
2
0
08 Jul 2024
Causal Discovery with Fewer Conditional Independence Tests
Causal Discovery with Fewer Conditional Independence Tests
Kirankumar Shiragur
Jiaqi Zhang
Caroline Uhler
CML
51
2
0
03 Jun 2024
Hyperplane Representations of Interventional Characteristic Imset
  Polytopes
Hyperplane Representations of Interventional Characteristic Imset Polytopes
Benjamin Hollering
Joseph Johnson
Liam Solus
114
0
0
29 Apr 2024
Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models
Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models
Tong Xu
Armeen Taeb
Simge Kuccukyavuz
Ali Shojaie
CML
147
1
0
19 Apr 2024
Colored Gaussian DAG models
Colored Gaussian DAG models
Tobias Boege
Kaie Kubjas
Pratik Misra
Liam Solus
72
0
0
05 Apr 2024
Recursive Causal Discovery
Recursive Causal Discovery
Ehsan Mokhtarian
Sepehr Elahi
S. Akbari
Negar Kiyavash
CML
77
2
0
14 Mar 2024
Membership Testing in Markov Equivalence Classes via Independence Query
  Oracles
Membership Testing in Markov Equivalence Classes via Independence Query Oracles
Jiaqi Zhang
Kirankumar Shiragur
Caroline Uhler
CML
68
0
0
09 Mar 2024
Learning Linear Gaussian Polytree Models with Interventions
Learning Linear Gaussian Polytree Models with Interventions
D. Tramontano
L. Waldmann
Mathias Drton
Eliana Duarte
48
0
0
08 Nov 2023
Sample Complexity Bounds for Score-Matching: Causal Discovery and
  Generative Modeling
Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling
Zhenyu Zhu
Francesco Locatello
Volkan Cevher
74
7
0
27 Oct 2023
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score
  Search and Grow-Shrink Trees
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow-Shrink Trees
Bryan Andrews
Joseph Ramsey
Ruben Sanchez-Romero
Jazmin Camchong
Erich Kummerfeld
CML
64
18
0
26 Oct 2023
On sample complexity of conditional independence testing with Von Mises
  estimator with application to causal discovery
On sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery
Fateme Jamshidi
Luca Ganassali
Negar Kiyavash
56
4
0
20 Oct 2023
Differentiable Bayesian Structure Learning with Acyclicity Assurance
Differentiable Bayesian Structure Learning with Acyclicity Assurance
Quang-Duy Tran
Phuoc Nguyen
Bao Duong
Thin Nguyen
76
2
0
04 Sep 2023
Hierarchical Topological Ordering with Conditional Independence Test for
  Limited Time Series
Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series
Anpeng Wu
Haoxuan Li
Kun Kuang
Ke Zhang
Leilei Gan
CML
114
2
0
16 Aug 2023
Order-based Structure Learning with Normalizing Flows
Order-based Structure Learning with Normalizing Flows
Hamidreza Kamkari
Vahid Balazadeh Meresht
Vahid Zehtab
Rahul G. Krishnan
CML
87
3
0
14 Aug 2023
Identifiability Guarantees for Causal Disentanglement from Soft
  Interventions
Identifiability Guarantees for Causal Disentanglement from Soft Interventions
Jiaqi Zhang
C. Squires
Kristjan Greenewald
Akash Srivastava
Karthikeyan Shanmugam
Caroline Uhler
CML
129
65
0
12 Jul 2023
Active causal structure learning with advice
Active causal structure learning with advice
Davin Choo
Themis Gouleakis
Arnab Bhattacharyya
CML
72
3
0
31 May 2023
Optimizing NOTEARS Objectives via Topological Swaps
Optimizing NOTEARS Objectives via Topological Swaps
Chang Deng
Kevin Bello
Bryon Aragam
Pradeep Ravikumar
20
14
0
26 May 2023
A Survey on Causal Discovery: Theory and Practice
A Survey on Causal Discovery: Theory and Practice
Alessio Zanga
Fabio Stella
CML
77
45
0
17 May 2023
Causal Razors
Causal Razors
Wai-yin Lam
CML
65
0
0
20 Feb 2023
CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary
  Time Series Data
CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data
Muhammad Hasan Ferdous
Uzma Hasan
Md. Osman Gani
CML
64
3
0
07 Feb 2023
Learning Large Causal Structures from Inverse Covariance Matrix via
  Sparse Matrix Decomposition
Learning Large Causal Structures from Inverse Covariance Matrix via Sparse Matrix Decomposition
Shuyu Dong
Kento Uemura
Akito Fujii
Shuang Chang
Yusuke Koyanagi
Koji Maruhashi
Michèle Sebag
CML
28
1
0
25 Nov 2022
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and
  Variational Bayes
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes
Mizu Nishikawa-Toomey
T. Deleu
Jithendaraa Subramanian
Yoshua Bengio
Laurent Charlin
BDLCML
111
29
0
04 Nov 2022
Diffusion Models for Causal Discovery via Topological Ordering
Diffusion Models for Causal Discovery via Topological Ordering
Pedro Sanchez
Xiao Liu
Alison Q. OÑeil
Sotirios A. Tsaftaris
DiffM
149
49
0
12 Oct 2022
On the Edges of Characteristic Imset Polytopes
On the Edges of Characteristic Imset Polytopes
Svante Linusson
Petter Restadh
Liam Solus
CVBM
29
6
0
15 Sep 2022
Active Learning for Optimal Intervention Design in Causal Models
Active Learning for Optimal Intervention Design in Causal Models
Jiaqi Zhang
Louis V. Cammarata
C. Squires
T. Sapsis
Caroline Uhler
CML
109
28
0
10 Sep 2022
Toric Ideals of Characteristic Imsets via Quasi-Independence Gluing
Toric Ideals of Characteristic Imsets via Quasi-Independence Gluing
Benjamin Hollering
Joseph Johnson
Irem Portakal
Liam Solus
23
1
0
05 Sep 2022
Large-Scale Differentiable Causal Discovery of Factor Graphs
Large-Scale Differentiable Causal Discovery of Factor Graphs
Romain Lopez
Jan-Christian Hütter
J. Pritchard
Aviv Regev
CMLAI4CE
87
43
0
15 Jun 2022
Greedy Relaxations of the Sparsest Permutation Algorithm
Greedy Relaxations of the Sparsest Permutation Algorithm
Wai-yin Lam
Bryan Andrews
Joseph Ramsey
82
48
0
11 Jun 2022
Causal Structure Learning: a Combinatorial Perspective
Causal Structure Learning: a Combinatorial Perspective
C. Squires
Caroline Uhler
CML
120
47
0
02 Jun 2022
PAC Generalization via Invariant Representations
PAC Generalization via Invariant Representations
Advait Parulekar
Karthikeyan Shanmugam
Sanjay Shakkottai
93
4
0
30 May 2022
Score matching enables causal discovery of nonlinear additive noise
  models
Score matching enables causal discovery of nonlinear additive noise models
Paul Rolland
Volkan Cevher
Matthäus Kleindessner
Chris Russel
Bernhard Schölkopf
Dominik Janzing
Francesco Locatello
CML
99
90
0
08 Mar 2022
Sequentially learning the topological ordering of causal directed
  acyclic graphs with likelihood ratio scores
Sequentially learning the topological ordering of causal directed acyclic graphs with likelihood ratio scores
Gabriel Ruiz
Oscar Hernan Madrid Padilla
Qing Zhou
CML
68
2
0
03 Feb 2022
BCDAG: An R package for Bayesian structure and Causal learning of
  Gaussian DAGs
BCDAG: An R package for Bayesian structure and Causal learning of Gaussian DAGs
F. Castelletti
Alessandro Mascaro
CML
52
3
0
28 Jan 2022
Learning Bayesian Networks in the Presence of Structural Side
  Information
Learning Bayesian Networks in the Presence of Structural Side Information
Ehsan Mokhtarian
S. Akbari
Fatemeh Jamshidi
Jalal Etesami
Negar Kiyavash
63
16
0
20 Dec 2021
Variance Minimization in the Wasserstein Space for Invariant Causal
  Prediction
Variance Minimization in the Wasserstein Space for Invariant Causal Prediction
Guillaume Martinet
Alexander Strzalkowski
Barbara E. Engelhardt
BDLOOD
48
7
0
13 Oct 2021
A survey of Bayesian Network structure learning
A survey of Bayesian Network structure learning
N. K. Kitson
Anthony C. Constantinou
Zhi-gao Guo
Yang Liu
Kiattikun Chobtham
CML
106
198
0
23 Sep 2021
Benchpress: A Scalable and Versatile Workflow for Benchmarking Structure
  Learning Algorithms
Benchpress: A Scalable and Versatile Workflow for Benchmarking Structure Learning Algorithms
Felix L. Rios
G. Moffa
Jack Kuipers
CML
98
12
0
08 Jul 2021
A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under
  the k-Triangle-Faithfulness Assumption
A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the k-Triangle-Faithfulness Assumption
Shuyan Wang
Peter Spirtes
19
1
0
03 Jul 2021
Definite Non-Ancestral Relations and Structure Learning
Definite Non-Ancestral Relations and Structure Learning
Wenyu Chen
Mathias Drton
Ali Shojaie
CML
47
1
0
20 May 2021
Ordering-Based Causal Discovery with Reinforcement Learning
Ordering-Based Causal Discovery with Reinforcement Learning
Xiaoqiang Wang
Yali Du
Shengyu Zhu
Liangjun Ke
Zhitang Chen
Jianye Hao
Jun Wang
CML
84
64
0
14 May 2021
Greedy Causal Discovery is Geometric
Greedy Causal Discovery is Geometric
Svante Linusson
Petter Restadh
Liam Solus
CML
120
10
0
05 Mar 2021
Batch Bayesian Optimization on Permutations using the Acquisition
  Weighted Kernel
Batch Bayesian Optimization on Permutations using the Acquisition Weighted Kernel
Changyong Oh
Roberto Bondesan
E. Gavves
Max Welling
54
6
0
26 Feb 2021
Complexity analysis of Bayesian learning of high-dimensional DAG models
  and their equivalence classes
Complexity analysis of Bayesian learning of high-dimensional DAG models and their equivalence classes
Quan Zhou
Hyunwoong Chang
121
12
0
11 Jan 2021
Efficient Permutation Discovery in Causal DAGs
Efficient Permutation Discovery in Causal DAGs
C. Squires
Joshua Amaniampong
Caroline Uhler
CML
41
4
0
06 Nov 2020
A Recursive Markov Boundary-Based Approach to Causal Structure Learning
A Recursive Markov Boundary-Based Approach to Causal Structure Learning
Ehsan Mokhtarian
S. Akbari
AmirEmad Ghassami
Negar Kiyavash
CML
46
17
0
10 Oct 2020
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