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Self-Compatibility: Evaluating Causal Discovery without Ground Truth

Self-Compatibility: Evaluating Causal Discovery without Ground Truth

18 July 2023
P. M. Faller
L. C. Vankadara
Atalanti A. Mastakouri
Francesco Locatello
Dominik Janzing Karlsruhe Institute of Technology
    CML
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Papers citing "Self-Compatibility: Evaluating Causal Discovery without Ground Truth"

13 / 13 papers shown
Title
Meta-Dependence in Conditional Independence Testing
Meta-Dependence in Conditional Independence Testing
Bijan Mazaheri
Jiaqi Zhang
Caroline Uhler
CML
51
0
0
17 Apr 2025
CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series
CausalRivers -- Scaling up benchmarking of causal discovery for real-world time-series
Gideon Stein
M. Shadaydeh
Jan Blunk
Niklas Penzel
Joachim Denzler
AI4TS
42
0
0
21 Mar 2025
Causal Modeling in Multi-Context Systems: Distinguishing Multiple
  Context-Specific Causal Graphs which Account for Observational Support
Causal Modeling in Multi-Context Systems: Distinguishing Multiple Context-Specific Causal Graphs which Account for Observational Support
Martin Rabel
Wiebke Günther
Jakob Runge
Andreas Gerhardus
11
0
0
27 Oct 2024
LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery
LoSAM: Local Search in Additive Noise Models with Mixed Mechanisms and General Noise for Global Causal Discovery
Sujai Hiremath
Promit Ghosal
Kyra Gan
CML
32
0
0
15 Oct 2024
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning
Ashka Shah
Adela DePavia
Nathaniel Hudson
Ian T. Foster
Rick L. Stevens
CML
31
1
0
10 Jun 2024
Learning Structural Causal Models through Deep Generative Models:
  Methods, Guarantees, and Challenges
Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges
Audrey Poinsot
Alessandro Leite
Nicolas Chesneau
Michèle Sébag
Marc Schoenauer
54
3
0
08 May 2024
Sample, estimate, aggregate: A recipe for causal discovery foundation models
Sample, estimate, aggregate: A recipe for causal discovery foundation models
Menghua Wu
Yujia Bao
Regina Barzilay
Tommi Jaakkola
CML
49
7
0
02 Feb 2024
Learned Causal Method Prediction
Learned Causal Method Prediction
Shantanu Gupta
Cheng Zhang
Agrin Hilmkil
OOD
38
2
0
07 Nov 2023
Toward Falsifying Causal Graphs Using a Permutation-Based Test
Toward Falsifying Causal Graphs Using a Permutation-Based Test
Elias Eulig
Atalanti A. Mastakouri
Patrick Blobaum
Michael W. Hardt
Dominik Janzing
13
8
0
16 May 2023
Causal Inference Through the Structural Causal Marginal Problem
Causal Inference Through the Structural Causal Marginal Problem
Luigi Gresele
Julius von Kügelgen
Jonas M. Kubler
Elke Kirschbaum
Bernhard Schölkopf
Dominik Janzing
22
19
0
02 Feb 2022
Learning Sparse Nonparametric DAGs
Learning Sparse Nonparametric DAGs
Xun Zheng
Chen Dan
Bryon Aragam
Pradeep Ravikumar
Eric P. Xing
CML
111
258
0
29 Sep 2019
Estimating and Controlling the False Discovery Rate for the PC Algorithm
  Using Edge-Specific P-Values
Estimating and Controlling the False Discovery Rate for the PC Algorithm Using Edge-Specific P-Values
Eric V. Strobl
Peter Spirtes
Shyam Visweswaran
37
18
0
14 Jul 2016
Causal Inference in the Presence of Latent Variables and Selection Bias
Causal Inference in the Presence of Latent Variables and Selection Bias
Peter Spirtes
Christopher Meek
Thomas S. Richardson
CML
147
435
0
20 Feb 2013
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