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Geometry of the faithfulness assumption in causal inference
v1v2v3 (latest)

Geometry of the faithfulness assumption in causal inference

2 July 2012
Caroline Uhler
Garvesh Raskutti
Peter Buhlmann
B. Yu
ArXiv (abs)PDFHTML

Papers citing "Geometry of the faithfulness assumption in causal inference"

50 / 103 papers shown
Learning Gaussian DAG Models without Condition Number Bounds
Learning Gaussian DAG Models without Condition Number Bounds
Constantinos Daskalakis
Vardis Kandiros
Rui-Min Yao
126
3
0
08 Nov 2025
Causal Structure and Representation Learning with Biomedical Applications
Causal Structure and Representation Learning with Biomedical Applications
Caroline Uhler
Jiaqi Zhang
CMLOOD
340
1
0
06 Nov 2025
Consistent Bayesian causal discovery for structural equation models with equal error variances
Consistent Bayesian causal discovery for structural equation models with equal error variances
Anamitra Chaudhuri
Yang Ni
Anirban Bhattacharya
CML
103
0
0
18 Sep 2025
Causal Reasoning in Pieces: Modular In-Context Learning for Causal Discovery
Causal Reasoning in Pieces: Modular In-Context Learning for Causal Discovery
Kacper Kadziolka
Saber Salehkaleybar
ReLMCMLLRM
166
1
0
31 Jul 2025
dcFCI: Robust Causal Discovery Under Latent Confounding, Unfaithfulness, and Mixed Data
dcFCI: Robust Causal Discovery Under Latent Confounding, Unfaithfulness, and Mixed Data
Adèle H. Ribeiro
Dominik Heider
CML
223
1
0
10 May 2025
Local Markov Equivalence for PC-style Local Causal Discovery and Identification of Controlled Direct Effects
Local Markov Equivalence for PC-style Local Causal Discovery and Identification of Controlled Direct Effects
Timothée Loranchet
Charles K. Assaad
CML
314
1
0
05 May 2025
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects
Praharsh Nanavati
Ranjitha Prasad
Karthikeyan Shanmugam
OODCML
326
0
0
29 Apr 2025
Meta-Dependence in Conditional Independence Testing
Meta-Dependence in Conditional Independence Testing
Bijan Mazaheri
Jiaqi Zhang
Caroline Uhler
CML
257
2
0
17 Apr 2025
Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Mateusz Olko
Mateusz Gajewski
Joanna Wojciechowska
Mikołaj Morzy
Piotr Sankowski
Piotr Miłoś
CML
389
4
0
22 Feb 2025
No Foundations without Foundations -- Why semi-mechanistic models are essential for regulatory biology
No Foundations without Foundations -- Why semi-mechanistic models are essential for regulatory biology
Luka Kovacevic
Thomas Gaudelet
James Opzoomer
Hagen Triendl
John Whittaker
Caroline Uhler
Lindsay Edwards
J. Taylor-King
AI4CE
322
2
0
31 Jan 2025
Choosing DAG Models Using Markov and Minimal Edge Count in the Absence
  of Ground Truth
Choosing DAG Models Using Markov and Minimal Edge Count in the Absence of Ground Truth
Joseph Ramsey
Bryan Andrews
Peter Spirtes
CML
254
4
0
30 Sep 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
400
1
0
21 Aug 2024
A General Framework on Conditions for Constraint-based Causal Learning
A General Framework on Conditions for Constraint-based Causal LearningScandinavian Journal of Statistics (Scand. J. Stat.), 2024
Kai Z. Teh
Kayvan Sadeghi
Terry Soo
CML
247
1
0
14 Aug 2024
Score matching through the roof: linear, nonlinear, and latent variables causal discovery
Score matching through the roof: linear, nonlinear, and latent variables causal discovery
Francesco Montagna
P. M. Faller
Patrick Bloebaum
Elke Kirschbaum
Francesco Locatello
CML
441
7
0
26 Jul 2024
Scalable and Flexible Causal Discovery with an Efficient Test for
  Adjacency
Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
Alan Nawzad Amin
Andrew Gordon Wilson
CML
476
4
0
13 Jun 2024
Demystifying amortized causal discovery with transformers
Demystifying amortized causal discovery with transformers
Francesco Montagna
Max Cairney-Leeming
Dhanya Sridhar
Francesco Locatello
CML
532
4
0
27 May 2024
Better Simulations for Validating Causal Discovery with the
  DAG-Adaptation of the Onion Method
Better Simulations for Validating Causal Discovery with the DAG-Adaptation of the Onion Method
Bryan Andrews
Erich Kummerfeld
CML
244
7
0
21 May 2024
Property testing in graphical models: testing small separation numbers
Property testing in graphical models: testing small separation numbers
Luc Devroye
Gábor Lugosi
Piotr Zwiernik
276
0
0
16 May 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
589
5
0
19 Apr 2024
Faithlessness in Gaussian graphical models
Faithlessness in Gaussian graphical models
Mathias Drton
Leonard Henckel
Benjamin Hollering
Pratik Misra
303
1
0
08 Apr 2024
Applied Causal Inference Powered by ML and AI
Applied Causal Inference Powered by ML and AI
Victor Chernozhukov
Christian Hansen
Nathan Kallus
Martin Spindler
Vasilis Syrgkanis
CML
438
57
0
04 Mar 2024
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery
Yang Chen
Yitao Liang
Zhouchen Lin
OODCML
261
0
0
29 Feb 2024
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes
Georg Manten
Cecilia Casolo
E. Ferrucci
Søren Wengel Mogensen
C. Salvi
Niki Kilbertus
CMLBDL
783
18
0
28 Feb 2024
Efficient adjustment for complex covariates: Gaining efficiency with DOPE
Efficient adjustment for complex covariates: Gaining efficiency with DOPE
Alexander Mangulad Christgau
Niels Richard Hansen
N. Hansen
349
7
0
20 Feb 2024
Optimal estimation of Gaussian (poly)trees
Optimal estimation of Gaussian (poly)trees
Yuhao Wang
Ming Gao
Wai Ming Tai
Bryon Aragam
Arnab Bhattacharyya
TPM
249
2
0
09 Feb 2024
Causal Representation Learning from Multiple Distributions: A General
  Setting
Causal Representation Learning from Multiple Distributions: A General Setting
Kun Zhang
Shaoan Xie
Ignavier Ng
Yujia Zheng
CMLOOD
471
56
0
07 Feb 2024
Bayesian Approach to Linear Bayesian Networks
Bayesian Approach to Linear Bayesian Networks
Seyong Hwang
Kyoungjae Lee
Sunmin Oh
Gunwoong Park
280
1
0
27 Nov 2023
Distributionally Robust Skeleton Learning of Discrete Bayesian Networks
Distributionally Robust Skeleton Learning of Discrete Bayesian NetworksNeural Information Processing Systems (NeurIPS), 2023
Yeshu Li
Brian Ziebart
OOD
238
1
0
10 Nov 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 TreesNeural Information Processing Systems (NeurIPS), 2023
Bryan Andrews
Joseph Ramsey
Ruben Sanchez-Romero
Jazmin Camchong
Erich Kummerfeld
CML
248
42
0
26 Oct 2023
Assumption violations in causal discovery and the robustness of score
  matching
Assumption violations in causal discovery and the robustness of score matching
Francesco Montagna
Atalanti A. Mastakouri
Elias Eulig
Nicoletta Noceti
Lorenzo Rosasco
Dominik Janzing
Bryon Aragam
Francesco Locatello
OOD
268
29
0
20 Oct 2023
Expert-Aided Causal Discovery of Ancestral Graphs
Expert-Aided Causal Discovery of Ancestral Graphs
Tiago da Silva
Bruna Bazaluk
Eliezer de Souza da Silva
António Góis
Dominik Heider
Samuel Kaski
Diego Mesquita
Adèle H. Ribeiro
Adèle Helena Ribeiro
CML
553
7
0
21 Sep 2023
Partially Specified Causal Simulations
Partially Specified Causal Simulations
Alireza Zamanian
Leopold Mareis
Narges Ahmidi
CML
282
1
0
19 Sep 2023
Identifiability Guarantees for Causal Disentanglement from Soft
  Interventions
Identifiability Guarantees for Causal Disentanglement from Soft InterventionsNeural Information Processing Systems (NeurIPS), 2023
Jiaqi Zhang
C. Squires
Kristjan Greenewald
Akash Srivastava
Karthikeyan Shanmugam
Caroline Uhler
CML
462
97
0
12 Jul 2023
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive
  Noise Models
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise ModelsNeural Information Processing Systems (NeurIPS), 2023
Tianyu Chen
Kevin Bello
Bryon Aragam
Pradeep Ravikumar
CML
393
5
0
30 Jun 2023
$\texttt{causalAssembly}$: Generating Realistic Production Data for
  Benchmarking Causal Discovery
causalAssembly\texttt{causalAssembly}causalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery
Konstantin Göbler
Tobias Windisch
Mathias Drton
T. Pychynski
Steffen Sonntag
Martin Roth
CML
512
18
0
19 Jun 2023
Explaining Predictive Uncertainty with Information Theoretic Shapley
  Values
Explaining Predictive Uncertainty with Information Theoretic Shapley ValuesNeural Information Processing Systems (NeurIPS), 2023
David S. Watson
Joshua O'Hara
Niek Tax
Richard Mudd
Ido Guy
TDIFAtt
359
45
0
09 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown
  Interventions
Nonparametric Identifiability of Causal Representations from Unknown InterventionsNeural Information Processing Systems (NeurIPS), 2023
Julius von Kügelgen
M. Besserve
Wendong Liang
Luigi Gresele
Armin Kekić
Elias Bareinboim
David M. Blei
Bernhard Schölkopf
CML
568
93
0
01 Jun 2023
Active causal structure learning with advice
Active causal structure learning with adviceInternational Conference on Machine Learning (ICML), 2023
Davin Choo
Themis Gouleakis
Arnab Bhattacharyya
CML
260
8
0
31 May 2023
Toward Falsifying Causal Graphs Using a Permutation-Based Test
Toward Falsifying Causal Graphs Using a Permutation-Based TestAAAI Conference on Artificial Intelligence (AAAI), 2023
Elias Eulig
Atalanti A. Mastakouri
Patrick Blobaum
Michael W. Hardt
Dominik Janzing
196
20
0
16 May 2023
Reinterpreting causal discovery as the task of predicting unobserved
  joint statistics
Reinterpreting causal discovery as the task of predicting unobserved joint statistics
Dominik Janzing
P. M. Faller
L. C. Vankadara
CML
406
4
0
11 May 2023
Causal Razors
Causal Razors
Wai-yin Lam
CML
479
0
0
20 Feb 2023
Local Causal Discovery for Estimating Causal Effects
Local Causal Discovery for Estimating Causal EffectsCLEaR (CLEaR), 2023
Shantanu Gupta
David Benjamin Childers
Zachary Chase Lipton
CML
621
16
0
16 Feb 2023
Subset verification and search algorithms for causal DAGs
Subset verification and search algorithms for causal DAGsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Davin Choo
Kirankumar Shiragur
CML
477
14
0
09 Jan 2023
Robust Model Selection of Gaussian Graphical Models
Robust Model Selection of Gaussian Graphical Models
Abrar Zahin
Rajasekhar Anguluri
Lalitha Sankar
O. Kosut
Gautam Dasarathy
275
0
0
10 Nov 2022
A Review and Roadmap of Deep Learning Causal Discovery in Different
  Variable Paradigms
A Review and Roadmap of Deep Learning Causal Discovery in Different Variable Paradigms
Hang Chen
Keqing Du
Xinyu Yang
Chenguang Li
CML
235
14
0
14 Sep 2022
Domain Knowledge in A*-Based Causal Discovery
Domain Knowledge in A*-Based Causal Discovery
Steven Kleinegesse
A. Lawrence
Hana Chockler
CML
164
4
0
17 Aug 2022
Large-Scale Differentiable Causal Discovery of Factor Graphs
Large-Scale Differentiable Causal Discovery of Factor GraphsNeural Information Processing Systems (NeurIPS), 2022
Romain Lopez
Jan-Christian Hütter
J. Pritchard
Aviv Regev
CMLAI4CE
471
62
0
15 Jun 2022
Differentiable and Transportable Structure Learning
Differentiable and Transportable Structure LearningInternational Conference on Machine Learning (ICML), 2022
Jeroen Berrevoets
Nabeel Seedat
F. Imrie
M. Schaar
472
4
0
13 Jun 2022
Greedy Relaxations of the Sparsest Permutation Algorithm
Greedy Relaxations of the Sparsest Permutation AlgorithmConference on Uncertainty in Artificial Intelligence (UAI), 2022
Wai-yin Lam
Bryan Andrews
Joseph Ramsey
401
75
0
11 Jun 2022
Causal Structure Learning: a Combinatorial Perspective
Causal Structure Learning: a Combinatorial PerspectiveFoundations of Computational Mathematics (FoCM), 2022
C. Squires
Caroline Uhler
CML
546
66
0
02 Jun 2022
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