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From Statistical to Causal Learning

From Statistical to Causal Learning

1 April 2022
Bernhard Schölkopf
Julius von Kügelgen
    CML
ArXivPDFHTML

Papers citing "From Statistical to Causal Learning"

37 / 37 papers shown
Title
Causal invariant geographic network representations with feature and structural distribution shifts
Causal invariant geographic network representations with feature and structural distribution shifts
Yuhan Wang
Silu He
Qinyao Luo
Hongyuan Yuan
Ling Zhao
Jiawei Zhu
Haifeng Li
OOD
59
0
0
25 Mar 2025
A Causal Adjustment Module for Debiasing Scene Graph Generation
A Causal Adjustment Module for Debiasing Scene Graph Generation
Li Liu
Shuzhou Sun
Shuaifeng Zhi
Fan Shi
Zhen Liu
J. Heikkilä
Yongxiang Liu
CML
52
2
0
22 Mar 2025
ExMAG: Learning of Maximally Ancestral Graphs
ExMAG: Learning of Maximally Ancestral Graphs
Petr Rysavý
Pavel Rytír
Xiaoyu He
Jakub Marecek
Georgios Korpas
CML
64
0
0
11 Mar 2025
On The Causal Network Of Face-selective Regions In Human Brain During Movie Watching
On The Causal Network Of Face-selective Regions In Human Brain During Movie Watching
Ali Bavafa
Gholam-Ali Hossein-Zadeh
CML
CVBM
23
0
0
04 Jan 2025
Active Causal Structure Learning with Latent Variables: Towards Learning
  to Detour in Autonomous Robots
Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
Pablo de los Riscos
Fernando Corbacho
CML
18
0
0
28 Oct 2024
DICS: Find Domain-Invariant and Class-Specific Features for
  Out-of-Distribution Generalization
DICS: Find Domain-Invariant and Class-Specific Features for Out-of-Distribution Generalization
Qiaowei Miao
Yawei Luo
Yi Yang
OOD
OODD
24
1
0
13 Sep 2024
Disentangled Representations for Causal Cognition
Disentangled Representations for Causal Cognition
Filippo Torresan
Manuel Baltieri
CML
27
1
0
30 Jun 2024
Identifiable Object-Centric Representation Learning via Probabilistic
  Slot Attention
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
Avinash Kori
Francesco Locatello
Ainkaran Santhirasekaram
Francesca Toni
Ben Glocker
Fabio De Sousa Ribeiro
OCL
40
1
0
11 Jun 2024
Learning Interpretable Concepts: Unifying Causal Representation Learning
  and Foundation Models
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models
Goutham Rajendran
Simon Buchholz
Bryon Aragam
Bernhard Schölkopf
Pradeep Ravikumar
AI4CE
83
21
0
14 Feb 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies
  and An Outlook
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
Wenzhao Jiang
Hao Liu
Hui Xiong
CML
AI4CE
28
2
0
19 Dec 2023
Sim-to-Real Causal Transfer: A Metric Learning Approach to
  Causally-Aware Interaction Representations
Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations
Yuejiang Liu
Ahmad Rahimi
Po-Chien Luan
Frano Rajic
Alexandre Alahi
25
3
0
07 Dec 2023
Causality and Explainability for Trustworthy Integrated Pest Management
Causality and Explainability for Trustworthy Integrated Pest Management
Ilias Tsoumas
Vasileios Sitokonstantinou
Georgios Giannarakis
Evagelia Lampiri
C. Athanassiou
Gustau Camps-Valls
C. Kontoes
Ioannis Athanasiadis
18
2
0
07 Dec 2023
Concept-free Causal Disentanglement with Variational Graph Auto-Encoder
Concept-free Causal Disentanglement with Variational Graph Auto-Encoder
Jingyun Feng
Lin Zhang
Lili Yang
BDL
CoGe
CML
19
1
0
17 Nov 2023
From Identifiable Causal Representations to Controllable Counterfactual
  Generation: A Survey on Causal Generative Modeling
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling
Aneesh Komanduri
Xintao Wu
Yongkai Wu
Feng Chen
CML
OOD
31
7
0
17 Oct 2023
Finding emergence in data by maximizing effective information
Finding emergence in data by maximizing effective information
Mingzhe Yang
Zhipeng Wang
Kaiwei Liu
Ying Rong
Bing Yuan
Jiang Zhang
CML
7
6
0
19 Aug 2023
Unbiased Scene Graph Generation via Two-stage Causal Modeling
Unbiased Scene Graph Generation via Two-stage Causal Modeling
Shuzhou Sun
Shuaifeng Zhi
Qing Liao
J. Heikkilä
Li Liu
CML
19
33
0
11 Jul 2023
Conditionally Invariant Representation Learning for Disentangling
  Cellular Heterogeneity
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity
H. Aliee
Ferdinand Kapl
Soroor Hediyeh-zadeh
Fabian J. Theis
CML
18
6
0
02 Jul 2023
Learning Linear Causal Representations from Interventions under General
  Nonlinear Mixing
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
Simon Buchholz
Goutham Rajendran
Elan Rosenfeld
Bryon Aragam
Bernhard Schölkopf
Pradeep Ravikumar
CML
32
57
0
04 Jun 2023
Learning Causally Disentangled Representations via the Principle of
  Independent Causal Mechanisms
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms
Aneesh Komanduri
Yongkai Wu
Feng Chen
Xintao Wu
CML
OOD
13
9
0
02 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown
  Interventions
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Julius von Kügelgen
M. Besserve
Wendong Liang
Luigi Gresele
Armin Kekić
Elias Bareinboim
David M. Blei
Bernhard Schölkopf
CML
16
56
0
01 Jun 2023
A Measure-Theoretic Axiomatisation of Causality
A Measure-Theoretic Axiomatisation of Causality
Junhyung Park
Simon Buchholz
Bernhard Schölkopf
Krikamol Muandet
24
5
0
19 May 2023
Enriching Disentanglement: From Logical Definitions to Quantitative
  Metrics
Enriching Disentanglement: From Logical Definitions to Quantitative Metrics
Yivan Zhang
Masashi Sugiyama
20
1
0
19 May 2023
A Review of the Role of Causality in Developing Trustworthy AI Systems
A Review of the Role of Causality in Developing Trustworthy AI Systems
Niloy Ganguly
Dren Fazlija
Maryam Badar
M. Fisichella
Sandipan Sikdar
...
Koustav Rudra
Manolis Koubarakis
Gourab K. Patro
W. Z. E. Amri
Wolfgang Nejdl
CML
28
23
0
14 Feb 2023
Toward a Theory of Causation for Interpreting Neural Code Models
Toward a Theory of Causation for Interpreting Neural Code Models
David Nader-Palacio
Alejandro Velasco
Nathan Cooper
Á. Rodríguez
Kevin Moran
Denys Poshyvanyk
20
16
0
07 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality
A Survey of Methods, Challenges and Perspectives in Causality
Gael Gendron
Michael Witbrock
Gillian Dobbie
OOD
AI4CE
CML
14
12
0
01 Feb 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
47
11
0
29 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
25
38
0
19 Jan 2023
Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image
  Classification
Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image Classification
Ming-Chang Chiu
Pin-Yu Chen
Xuezhe Ma
8
6
0
16 Dec 2022
Causal Inference via Style Transfer for Out-of-distribution
  Generalisation
Causal Inference via Style Transfer for Out-of-distribution Generalisation
Toan Nguyen
Kien Do
D. Nguyen
Bao Duong
T. Nguyen
CML
OODD
OOD
28
10
0
06 Dec 2022
Less Data, More Knowledge: Building Next Generation Semantic
  Communication Networks
Less Data, More Knowledge: Building Next Generation Semantic Communication Networks
Christina Chaccour
Walid Saad
Merouane Debbah
Zhu Han
H. Vincent Poor
GNN
3DV
24
119
0
25 Nov 2022
Backtracking Counterfactuals
Backtracking Counterfactuals
Julius von Kügelgen
Abdirisak Mohamed
Sander Beckers
LRM
27
16
0
01 Nov 2022
Conditional Independence Testing via Latent Representation Learning
Conditional Independence Testing via Latent Representation Learning
Bao Duong
T. Nguyen
BDL
CML
10
6
0
04 Sep 2022
Language-Based Causal Representation Learning
Language-Based Causal Representation Learning
Blai Bonet
Hector Geffner
22
0
0
12 Jul 2022
Weakly Supervised Representation Learning with Sparse Perturbations
Weakly Supervised Representation Learning with Sparse Perturbations
Kartik Ahuja
Jason S. Hartford
Yoshua Bengio
SSL
30
58
0
02 Jun 2022
On the Fairness of Causal Algorithmic Recourse
On the Fairness of Causal Algorithmic Recourse
Julius von Kügelgen
Amir-Hossein Karimi
Umang Bhatt
Isabel Valera
Adrian Weller
Bernhard Schölkopf
FaML
70
82
0
13 Oct 2020
From Ordinary Differential Equations to Structural Causal Models: the
  deterministic case
From Ordinary Differential Equations to Structural Causal Models: the deterministic case
Joris Mooij
Dominik Janzing
Bernhard Schölkopf
66
101
0
09 Aug 2014
Causal Inference and Causal Explanation with Background Knowledge
Causal Inference and Causal Explanation with Background Knowledge
Christopher Meek
CML
216
626
0
20 Feb 2013
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