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Score matching enables causal discovery of nonlinear additive noise
  models

Score matching enables causal discovery of nonlinear additive noise models

8 March 2022
Paul Rolland
V. Cevher
Matthäus Kleindessner
Chris Russel
Bernhard Schölkopf
Dominik Janzing
Francesco Locatello
    CML
ArXivPDFHTML

Papers citing "Score matching enables causal discovery of nonlinear additive noise models"

50 / 56 papers shown
Title
Proper scoring rules for estimation and forecast evaluation
Proper scoring rules for estimation and forecast evaluation
Kartik Waghmare
Johanna Ziegel
AI4TS
33
0
0
02 Apr 2025
CAUSAL3D: A Comprehensive Benchmark for Causal Learning from Visual Data
Disheng Liu
Yiran Qiao
Wuche Liu
Yiren Lu
Yunlai Zhou
Tuo Liang
Yu Yin
Jing Ma
CML
3DV
61
0
0
06 Mar 2025
Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery
Mateusz Olko
Mateusz Gajewski
Joanna Wojciechowska
Mikołaj Morzy
Piotr Sankowski
Piotr Miłoś
CML
47
0
0
22 Feb 2025
Causal Discovery via Bayesian Optimization
Bao Duong
Sunil Gupta
Thin Nguyen
44
0
0
28 Jan 2025
Identification of Nonparametric Dynamic Causal Structure and Latent Process in Climate System
Identification of Nonparametric Dynamic Causal Structure and Latent Process in Climate System
Minghao Fu
Biwei Huang
Zijian Li
Yujia Zheng
Ignavier Ng
Yingyao Hu
Kun Zhang
CML
50
0
0
21 Jan 2025
From Correlation to Causation: Understanding Climate Change through
  Causal Analysis and LLM Interpretations
From Correlation to Causation: Understanding Climate Change through Causal Analysis and LLM Interpretations
Shan Shan
AI4CE
72
1
0
21 Dec 2024
Exploring Multi-Modal Integration with Tool-Augmented LLM Agents for
  Precise Causal Discovery
Exploring Multi-Modal Integration with Tool-Augmented LLM Agents for Precise Causal Discovery
ChengAo Shen
Z. Chen
Dongsheng Luo
Dongkuan Xu
Haifeng Chen
Jingchao Ni
85
3
0
18 Dec 2024
Identifiability Guarantees for Causal Disentanglement from Purely
  Observational Data
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data
Ryan Welch
Jiaqi Zhang
Caroline Uhler
CML
OOD
51
1
0
31 Oct 2024
Causal Order Discovery based on Monotonic SCMs
Causal Order Discovery based on Monotonic SCMs
Ali Izadi
Martin Ester
31
0
0
24 Oct 2024
Efficient Differentiable Discovery of Causal Order
Efficient Differentiable Discovery of Causal Order
Mathieu Chevalley
Arash Mehrjou
Patrick Schwab
45
0
0
11 Oct 2024
Ordering-Based Causal Discovery for Linear and Nonlinear Relations
Ordering-Based Causal Discovery for Linear and Nonlinear Relations
Zhuopeng Xu
Yujie Li
Cheng Liu
Ning Gui
29
1
0
08 Oct 2024
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
Yingyu Lin
Yuxing Huang
Wenqin Liu
Haoran Deng
Ignavier Ng
Kun Zhang
Mingming Gong
Yi-An Ma
Biwei Huang
33
1
0
08 Oct 2024
Efficient Identification of Direct Causal Parents via Invariance and
  Minimum Error Testing
Efficient Identification of Direct Causal Parents via Invariance and Minimum Error Testing
Minh Le Nguyen
Mert R. Sabuncu
27
1
0
19 Sep 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
87
0
0
26 Jul 2024
Enabling Causal Discovery in Post-Nonlinear Models with Normalizing
  Flows
Enabling Causal Discovery in Post-Nonlinear Models with Normalizing Flows
Nu Hoang
Bao Duong
Thin Nguyen
35
0
0
06 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
34
1
0
13 Jun 2024
OCDB: Revisiting Causal Discovery with a Comprehensive Benchmark and
  Evaluation Framework
OCDB: Revisiting Causal Discovery with a Comprehensive Benchmark and Evaluation Framework
Wei Zhou
Hong Huang
Guowen Zhang
Ruize Shi
Kehan Yin
Yuanyuan Lin
Bang Liu
CML
50
1
0
07 Jun 2024
Deriving Causal Order from Single-Variable Interventions: Guarantees &
  Algorithm
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm
Mathieu Chevalley
Patrick Schwab
Arash Mehrjou
46
1
0
28 May 2024
Demystifying amortized causal discovery with transformers
Demystifying amortized causal discovery with transformers
Francesco Montagna
Max Cairney-Leeming
Dhanya Sridhar
Francesco Locatello
CML
57
1
0
27 May 2024
Amortized Active Causal Induction with Deep Reinforcement Learning
Amortized Active Causal Induction with Deep Reinforcement Learning
Yashas Annadani
P. Tigas
Stefan Bauer
Adam Foster
34
0
0
26 May 2024
From Probability to Counterfactuals: the Increasing Complexity of Satisfiability in Pearl's Causal Hierarchy
From Probability to Counterfactuals: the Increasing Complexity of Satisfiability in Pearl's Causal Hierarchy
Julian Dörfler
Benito van der Zander
Markus Bläser
Maciej Liskiewicz
LRM
28
1
0
12 May 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
CML
BDL
44
8
0
28 Feb 2024
Adjustment Identification Distance: A gadjid for Causal Structure
  Learning
Adjustment Identification Distance: A gadjid for Causal Structure Learning
Leonard Henckel
Theo Würtzen
Sebastian Weichwald
CML
32
6
0
13 Feb 2024
Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach
Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach
Masayuki Takayama
Tadahisa Okuda
Thong Pham
T. Ikenoue
Shingo Fukuma
Shohei Shimizu
Akiyoshi Sannai
79
16
0
02 Feb 2024
Shapley-PC: Constraint-based Causal Structure Learning with a Shapley Inspired Framework
Shapley-PC: Constraint-based Causal Structure Learning with a Shapley Inspired Framework
Fabrizio Russo
Francesca Toni
22
0
0
18 Dec 2023
Stable Differentiable Causal Discovery
Stable Differentiable Causal Discovery
Achille Nazaret
Justin Hong
Elham Azizi
David M. Blei
CML
23
9
0
17 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
V. Cevher
40
6
0
27 Oct 2023
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around
  Exposure-Outcome Pairs
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs
Jacqueline R. M. A. Maasch
Weishen Pan
Shantanu Gupta
Volodymyr Kuleshov
Kyra Gan
Fei Wang
30
5
0
25 Oct 2023
General Identifiability and Achievability for Causal Representation
  Learning
General Identifiability and Achievability for Causal Representation Learning
Burak Varici
Emre Acartürk
Karthikeyan Shanmugam
A. Tajer
CML
35
16
0
24 Oct 2023
Shortcuts for causal discovery of nonlinear models by score matching
Shortcuts for causal discovery of nonlinear models by score matching
Francesco Montagna
Nicoletta Noceti
Lorenzo Rosasco
Francesco Locatello
CML
53
3
0
22 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
20
17
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
32
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
Fei Wu
CML
6
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
29
1
0
14 Aug 2023
Diffusion Model in Causal Inference with Unmeasured Confounders
Diffusion Model in Causal Inference with Unmeasured Confounders
Tatsuhiro Shimizu
DiffM
21
4
0
07 Aug 2023
Heteroscedastic Causal Structure Learning
Heteroscedastic Causal Structure Learning
Bao Duong
T. Nguyen
CML
16
2
0
16 Jul 2023
A Causal Ordering Prior for Unsupervised Representation Learning
A Causal Ordering Prior for Unsupervised Representation Learning
Avinash Kori
Pedro Sanchez
Konstantinos Vilouras
Ben Glocker
Sotirios A. Tsaftaris
BDL
SSL
CML
32
0
0
11 Jul 2023
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive
  Noise Models
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models
Tianyu Chen
Kevin Bello
Bryon Aragam
Pradeep Ravikumar
CML
30
1
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
70
10
0
19 Jun 2023
Learning Causal Graphs via Monotone Triangular Transport Maps
Learning Causal Graphs via Monotone Triangular Transport Maps
S. Akbari
Luca Ganassali
Negar Kiyavash
OT
CML
16
8
0
26 May 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
Scalable Causal Discovery with Score Matching
Scalable Causal Discovery with Score Matching
Francesco Montagna
Nicoletta Noceti
Lorenzo Rosasco
Kun Zhang
Francesco Locatello
CML
52
25
0
06 Apr 2023
Causal Discovery with Score Matching on Additive Models with Arbitrary
  Noise
Causal Discovery with Score Matching on Additive Models with Arbitrary Noise
Francesco Montagna
Nicoletta Noceti
Lorenzo Rosasco
Kun Zhang
Francesco Locatello
CML
11
27
0
06 Apr 2023
A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive
  Noise Models
A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models
Alexander G. Reisach
Myriam Tami
C. Seiler
Antoine Chambaz
S. Weichwald
CML
36
19
0
31 Mar 2023
On Learning Necessary and Sufficient Causal Graphs
On Learning Necessary and Sufficient Causal Graphs
Hengrui Cai
Yixin Wang
Michael Jordan
Rui Song
CML
24
12
0
29 Jan 2023
On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs
On Heterogeneous Treatment Effects in Heterogeneous Causal Graphs
R. Watson
Hengrui Cai
X. An
S. Mclean
Rui Song
CML
13
2
0
29 Jan 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey
Emerging Synergies in Causality and Deep Generative Models: A Survey
Guanglin Zhou
Shaoan Xie
Guang-Yuan Hao
Shiming Chen
Biwei Huang
Xiwei Xu
Chen Wang
Liming Zhu
Lina Yao
Kun Zhang
AI4CE
53
11
0
29 Jan 2023
DAG Learning on the Permutahedron
DAG Learning on the Permutahedron
Valentina Zantedeschi
Luca Franceschi
Jean Kaddour
Matt J. Kusner
Vlad Niculae
27
11
0
27 Jan 2023
Score-based Causal Representation Learning with Interventions
Score-based Causal Representation Learning with Interventions
Burak Varici
Emre Acartürk
Karthikeyan Shanmugam
Abhishek Kumar
A. Tajer
CML
33
38
0
19 Jan 2023
Instrumental Variables in Causal Inference and Machine Learning: A
  Survey
Instrumental Variables in Causal Inference and Machine Learning: A Survey
Anpeng Wu
Kun Kuang
Ruoxuan Xiong
Fei Wu
SyDa
CML
25
6
0
12 Dec 2022
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