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Invariant Causal Prediction for Sequential Data
v1v2 (latest)

Invariant Causal Prediction for Sequential Data

25 June 2017
Niklas Pfister
Peter Buhlmann
J. Peters
    OOD
ArXiv (abs)PDFHTML

Papers citing "Invariant Causal Prediction for Sequential Data"

34 / 34 papers shown
Title
Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
Yaroslav Kivva
S. Akbari
Saber Salehkaleybar
Negar Kiyavash
CML
29
0
0
13 Jun 2025
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions
Juan L. Gamella
Armeen Taeb
C. Heinze-Deml
Peter Buhlmann
CML
187
8
0
13 Mar 2025
DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization
DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization
Jiaqi Wang
Yuhang Zhou
Zhixiong Zhang
Qiguang Chen
Yongqiang Chen
James Cheng
OODD
163
1
0
18 Feb 2025
Spatio-Temporal Graphical Counterfactuals: An Overview
Spatio-Temporal Graphical Counterfactuals: An Overview
Mingyu Kang
Duxin Chen
Ziyuan Pu
Jianxi Gao
Wenwu Yu
CML
107
1
0
02 Jul 2024
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning
Yihong Gu
Cong Fang
Peter Bühlmann
Jianqing Fan
OODCML
309
2
0
07 May 2024
Invariant Subspace Decomposition
Invariant Subspace Decomposition
Margherita Lazzaretto
Jonas Peters
Niklas Pfister
93
0
0
15 Apr 2024
Invariant Learning via Probability of Sufficient and Necessary Causes
Invariant Learning via Probability of Sufficient and Necessary Causes
Mengyue Yang
Zhen Fang
Yonggang Zhang
Yali Du
Furui Liu
Jean-François Ton
Jianhong Wang
Jun Wang
OODD
148
14
0
22 Sep 2023
Structural restrictions in local causal discovery: identifying direct causes of a target variable
Structural restrictions in local causal discovery: identifying direct causes of a target variable
Juraj Bodik
V. Chavez-Demoulin
CML
112
1
0
29 Jul 2023
AI for Anticipatory Action: Moving Beyond Climate Forecasting
AI for Anticipatory Action: Moving Beyond Climate Forecasting
Benjamin Q. Huynh
M. Kiang
AI4CE
62
0
0
28 Jul 2023
Discovering Causal Relations and Equations from Data
Discovering Causal Relations and Equations from Data
Gustau Camps-Valls
Andreas Gerhardus
Urmi Ninad
Gherardo Varando
Georg Martius
E. Balaguer-Ballester
Ricardo Vinuesa
Emiliano Díaz
L. Zanna
Jakob Runge
PINNAI4ClAI4CECML
108
77
0
21 May 2023
Out-of-Variable Generalization for Discriminative Models
Out-of-Variable Generalization for Discriminative Models
Siyuan Guo
J. Wildberger
Bernhard Schölkopf
OODCML
99
2
0
16 Apr 2023
Environment Invariant Linear Least Squares
Environment Invariant Linear Least Squares
Jianqing Fan
Cong Fang
Yihong Gu
Tong Zhang
OOD
119
13
0
06 Mar 2023
Generalized Invariant Matching Property via LASSO
Generalized Invariant Matching Property via LASSO
Kang Du
Yu Xiang
OOD
105
6
0
14 Jan 2023
Learning Invariant Representations under General Interventions on the
  Response
Learning Invariant Representations under General Interventions on the Response
Kang Du
Yu Xiang
OOD
103
8
0
22 Aug 2022
Equivariance and Invariance Inductive Bias for Learning from
  Insufficient Data
Equivariance and Invariance Inductive Bias for Learning from Insufficient Data
Tan Wang
Qianru Sun
Sugiri Pranata
J. Karlekar
Hanwang Zhang
SSL
100
21
0
25 Jul 2022
Probable Domain Generalization via Quantile Risk Minimization
Probable Domain Generalization via Quantile Risk Minimization
Cian Eastwood
Alexander Robey
Shashank Singh
Julius von Kügelgen
Hamed Hassani
George J. Pappas
Bernhard Schölkopf
OOD
121
67
0
20 Jul 2022
Out-of-distribution Generalization with Causal Invariant Transformations
Out-of-distribution Generalization with Causal Invariant Transformations
Ruoyu Wang
Mingyang Yi
Zhitang Chen
Shengyu Zhu
OODOODD
89
61
0
22 Mar 2022
Invariant Ancestry Search
Invariant Ancestry Search
Phillip B. Mogensen
Nikolaj Thams
J. Peters
96
5
0
02 Feb 2022
Understanding and Testing Generalization of Deep Networks on
  Out-of-Distribution Data
Understanding and Testing Generalization of Deep Networks on Out-of-Distribution Data
Rui Hu
Jitao Sang
Jinqiang Wang
Rui Hu
Chaoquan Jiang
CMLOOD
59
7
0
17 Nov 2021
Optimization-based Causal Estimation from Heterogenous Environments
Optimization-based Causal Estimation from Heterogenous Environments
Mingzhang Yin
Yixin Wang
David M. Blei
OOD
126
18
0
24 Sep 2021
Towards Out-Of-Distribution Generalization: A Survey
Towards Out-Of-Distribution Generalization: A Survey
Jiashuo Liu
Zheyan Shen
Yue He
Xingxuan Zhang
Renzhe Xu
Han Yu
Peng Cui
CMLOOD
168
536
0
31 Aug 2021
SHIFT15M: Fashion-specific dataset for set-to-set matching with several
  distribution shifts
SHIFT15M: Fashion-specific dataset for set-to-set matching with several distribution shifts
Masanari Kimura
Takuma Nakamura
Yuki Saito
OOD
94
3
0
30 Aug 2021
Invariant Policy Learning: A Causal Perspective
Invariant Policy Learning: A Causal Perspective
Sorawit Saengkyongam
Nikolaj Thams
J. Peters
Niklas Pfister
CMLOffRL
85
15
0
01 Jun 2021
Statistical Testing under Distributional Shifts
Statistical Testing under Distributional Shifts
Nikolaj Thams
Sorawit Saengkyongam
Niklas Pfister
J. Peters
OOD
124
10
0
22 May 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers
  Solutions with Superior OOD Generalization
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
Damien Teney
Ehsan Abbasnejad
Simon Lucey
Anton Van Den Hengel
113
90
0
12 May 2021
Towards Causal Representation Learning
Towards Causal Representation Learning
Bernhard Schölkopf
Francesco Locatello
Stefan Bauer
Nan Rosemary Ke
Nal Kalchbrenner
Anirudh Goyal
Yoshua Bengio
OODCMLAI4CE
155
322
0
22 Feb 2021
Causal Inference for Time series Analysis: Problems, Methods and
  Evaluation
Causal Inference for Time series Analysis: Problems, Methods and Evaluation
Raha Moraffah
Paras Sheth
Mansooreh Karami
Anchit Bhattacharya
Qianru Wang
Anique Tahir
A. Raglin
Huan Liu
CMLAI4TS
113
110
0
11 Feb 2021
Causal Inference from Slowly Varying Nonstationary Processes
Causal Inference from Slowly Varying Nonstationary Processes
Kang Du
Yu Xiang
109
6
0
23 Dec 2020
Invariant Representation Learning for Treatment Effect Estimation
Invariant Representation Learning for Treatment Effect Estimation
Claudia Shi
Victor Veitch
David M. Blei
OODCML
57
31
0
24 Nov 2020
Dirichlet policies for reinforced factor portfolios
Dirichlet policies for reinforced factor portfolios
Eric André
Guillaume Coqueret
85
7
0
10 Nov 2020
Differentiable Causal Discovery from Interventional Data
Differentiable Causal Discovery from Interventional Data
P. Brouillard
Sébastien Lachapelle
Alexandre Lacoste
Simon Lacoste-Julien
Alexandre Drouin
CML
99
191
0
03 Jul 2020
Active Invariant Causal Prediction: Experiment Selection through
  Stability
Active Invariant Causal Prediction: Experiment Selection through Stability
Juan L. Gamella
C. Heinze-Deml
OOD
61
46
0
10 Jun 2020
Orthogonal Structure Search for Efficient Causal Discovery from Observational Data
Anant Raj
Luigi Gresele
M. Besserve
Bernhard Schölkopf
Stefan Bauer
CML
27
0
0
06 Mar 2019
Switching Regression Models and Causal Inference in the Presence of
  Discrete Latent Variables
Switching Regression Models and Causal Inference in the Presence of Discrete Latent Variables
Rune Christiansen
J. Peters
CML
26
14
0
16 Aug 2018
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