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2204.00607
Cited By
From Statistical to Causal Learning
1 April 2022
Bernhard Schölkopf
Julius von Kügelgen
CML
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Papers citing
"From Statistical to Causal Learning"
36 / 36 papers shown
Identifiable Object Representations under Spatial Ambiguities
Avinash Kori
Francesca Toni
Ben Glocker
OCL
233
0
0
09 Jun 2025
Causal invariant geographic network representations with feature and structural distribution shifts
Future generations computer systems (FGCS), 2025
Yuhan Wang
Silu He
Qinyao Luo
Hongyuan Yuan
Ling Zhao
Jiawei Zhu
Haifeng Li
OOD
319
10
0
25 Mar 2025
A Causal Adjustment Module for Debiasing Scene Graph Generation
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025
Li Liu
Shuzhou Sun
Shuaifeng Zhi
Fan Shi
Zhen Liu
J. Heikkilä
Yongxiang Liu
CML
274
22
0
22 Mar 2025
ExMAG: Learning of Maximally Ancestral Graphs
Petr Rysavý
Pavel Rytíř
Xiaoyu He
Georgios Korpas
Georgios Korpas
CML
451
1
0
11 Mar 2025
On The Causal Network Of Face-selective Regions In Human Brain During Movie Watching
Ali Bavafa
Gholam-Ali Hossein-Zadeh
CML
CVBM
338
0
0
04 Jan 2025
Active Causal Structure Learning with Latent Variables: Towards Learning to Detour in Autonomous Robots
International Conference on Applied Informatics (ICAI), 2024
Pablo de los Riscos
Fernando Corbacho
CML
235
0
0
28 Oct 2024
DICS: Find Domain-Invariant and Class-Specific Features for Out-of-Distribution Generalization
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Qiaowei Miao
Yawei Luo
Yi Yang
OOD
OODD
185
2
0
13 Sep 2024
Disentangled Representations for Causal Cognition
Filippo Torresan
Manuel Baltieri
CML
264
4
0
30 Jun 2024
Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
Avinash Kori
Francesco Locatello
Ainkaran Santhirasekaram
Francesca Toni
Ben Glocker
Fabio De Sousa Ribeiro
OCL
277
8
0
11 Jun 2024
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models
Goutham Rajendran
Simon Buchholz
Bryon Aragam
Bernhard Schölkopf
Pradeep Ravikumar
AI4CE
406
30
0
14 Feb 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
Wenzhao Jiang
Hao Liu
Hui Xiong
CML
AI4CE
515
10
0
19 Dec 2023
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
130
4
0
07 Dec 2023
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
423
7
0
07 Dec 2023
Concept-free Causal Disentanglement with Variational Graph Auto-Encoder
Jingyun Feng
Lin Zhang
Lili Yang
BDL
CoGe
CML
225
2
0
17 Nov 2023
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling
Aneesh Komanduri
Xintao Wu
Yongkai Wu
Feng Chen
CML
OOD
464
23
0
17 Oct 2023
Finding emergence in data by maximizing effective information
National Science Review (NSR), 2023
Mingzhe Yang
Zhipeng Wang
Kaiwei Liu
Ying Rong
Bing Yuan
Jiang Zhang
CML
269
14
0
19 Aug 2023
Unbiased Scene Graph Generation via Two-stage Causal Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Shuzhou Sun
Shuaifeng Zhi
Qing Liao
J. Heikkilä
Tianpeng Liu
CML
261
51
0
11 Jul 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity
H. Aliee
Ferdinand Kapl
Soroor Hediyeh-zadeh
Fabian J. Theis
CML
286
9
0
02 Jul 2023
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
Neural Information Processing Systems (NeurIPS), 2023
Simon Buchholz
Goutham Rajendran
Elan Rosenfeld
Bryon Aragam
Bernhard Schölkopf
Pradeep Ravikumar
CML
370
77
0
04 Jun 2023
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms
International Joint Conference on Artificial Intelligence (IJCAI), 2023
Aneesh Komanduri
Yongkai Wu
Feng Chen
Xintao Wu
CML
OOD
465
17
0
02 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Neural Information Processing Systems (NeurIPS), 2023
Julius von Kügelgen
M. Besserve
Wendong Liang
Luigi Gresele
Armin Kekić
Elias Bareinboim
David M. Blei
Bernhard Schölkopf
CML
518
80
0
01 Jun 2023
A Measure-Theoretic Axiomatisation of Causality
Neural Information Processing Systems (NeurIPS), 2023
Junhyung Park
Simon Buchholz
Bernhard Schölkopf
Krikamol Muandet
339
8
0
19 May 2023
Enriching Disentanglement: From Logical Definitions to Quantitative Metrics
Neural Information Processing Systems (NeurIPS), 2023
Yivan Zhang
Masashi Sugiyama
285
2
0
19 May 2023
Counterfactual Learning on Graphs: A Survey
Machine Intelligence Research (MIR), 2023
Zhimeng Guo
Teng Xiao
Zongyu Wu
Charu C. Aggarwal
Hui Liu
Suhang Wang
CML
AI4CE
432
25
0
03 Apr 2023
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
323
27
0
14 Feb 2023
Toward a Theory of Causation for Interpreting Neural Code Models
IEEE Transactions on Software Engineering (TSE), 2023
David Nader-Palacio
Alejandro Velasco
Nathan Cooper
Á. Rodríguez
Kevin Moran
Denys Poshyvanyk
473
24
0
07 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality
Gaël Gendron
Michael Witbrock
Gillian Dobbie
OOD
AI4CE
CML
418
13
0
01 Feb 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey
Guanglin Zhou
Shaoan Xie
Guang-Yuan Hao
Shiming Chen
Erdun Gao
Xiwei Xu
Chen Wang
Liming Zhu
Lina Yao
Kun Zhang
AI4CE
467
14
0
29 Jan 2023
Score-based Causal Representation Learning with Interventions
Burak Varici
Emre Acartürk
Karthikeyan Shanmugam
Abhishek Kumar
A. Tajer
CML
346
47
0
19 Jan 2023
Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image Classification
IEEE International Conference on Computer Vision (ICCV), 2022
Ming-Chang Chiu
Pin-Yu Chen
Xuezhe Ma
236
7
0
16 Dec 2022
Causal Inference via Style Transfer for Out-of-distribution Generalisation
Knowledge Discovery and Data Mining (KDD), 2022
Toan Nguyen
Kien Do
D. Nguyen
Bao Duong
T. Nguyen
CML
OODD
OOD
222
15
0
06 Dec 2022
Less Data, More Knowledge: Building Next Generation Semantic Communication Networks
IEEE Communications Surveys and Tutorials (COMST), 2022
Christina Chaccour
Walid Saad
Merouane Debbah
Zhu Han
H. Vincent Poor
GNN
3DV
114
218
0
25 Nov 2022
Backtracking Counterfactuals
CLEaR (CLEaR), 2022
Julius von Kügelgen
Abdirisak Mohamed
Sander Beckers
LRM
312
27
0
01 Nov 2022
Conditional Independence Testing via Latent Representation Learning
Industrial Conference on Data Mining (IDM), 2022
Bao Duong
T. Nguyen
BDL
CML
197
8
0
04 Sep 2022
Language-Based Causal Representation Learning
Blai Bonet
Hector Geffner
250
0
0
12 Jul 2022
Weakly Supervised Representation Learning with Sparse Perturbations
Neural Information Processing Systems (NeurIPS), 2022
Kartik Ahuja
Jason S. Hartford
Yoshua Bengio
SSL
267
70
0
02 Jun 2022
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