Causal inference using invariant prediction: identification and confidence intervals

6 January 2015

Papers citing "Causal inference using invariant prediction: identification and confidence intervals"

50 / 206 papers shown

Title
Causality-Inspired Robustness for Nonlinear Models via Representation Learning Marin Šola Peter Bühlmann Xinwei Shen OOD 17 0 0 19 May 2025
Unsupervised Invariant Risk Minimization Yotam Norman Ron Meir OOD 19 0 0 18 May 2025
Bayesian Hierarchical Invariant Prediction Francisco Madaleno Pernille Julie Viuff Sand Francisco C. Pereira Sergio Hernan Garrido Mejia 24 0 0 16 May 2025
Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources Renzhe Xu Kun Wang Bo Li 41 0 0 12 May 2025
Characterization and Learning of Causal Graphs from Hard Interventions Zihan Zhou Muhammad Qasim Elahi Murat Kocaoglu CML 89 0 0 02 May 2025
Multi-Domain Causal Discovery in Bijective Causal Models Kasra Jalaldoust Saber Salehkaleybar Negar Kiyavash CML 79 0 0 30 Apr 2025
On the Value of Cross-Modal Misalignment in Multimodal Representation Learning Yichao Cai Yuhang Liu Erdun Gao Tianjiao Jiang Zhen Zhang Anton van den Hengel Javen Qinfeng Shi 64 0 0 14 Apr 2025
Partial Transportability for Domain Generalization Kasra Jalaldoust Alexis Bellot Elias Bareinboim OOD 80 5 0 30 Mar 2025
Characterization and Greedy Learning of Gaussian Structural Causal Models under Unknown Interventions Juan L. Gamella Armeen Taeb C. Heinze-Deml Peter Buhlmann CML 99 8 0 13 Mar 2025
Data Distributional Properties As Inductive Bias for Systematic Generalization Felipe del-Rio Alain Raymond-Sáez Daniel Florea Rodrigo Toro Icarte Julio Hurtado Cristian B. Calderon Á. Soto AI4CE 38 0 0 27 Feb 2025
DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization Jiaqi Wang Yuhang Zhou Zhixiong Zhang Qiguang Chen Yongqiang Chen James Cheng OODD 79 1 0 18 Feb 2025
Achievable distributional robustness when the robust risk is only partially identified Julia Kostin Nicola Gnecco Fanny Yang 80 3 0 04 Feb 2025
Empirical likelihood for Fréchet means on open books Karthik Bharath Huiling Le A. Wood Xi Yan 133 0 0 25 Dec 2024
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs Bowen Liu Haoyang Li Shuning Wang Shuo Nie Shanghang Zhang OODD CML 76 0 0 29 Oct 2024
Systems with Switching Causal Relations: A Meta-Causal Perspective Moritz Willig Tim Nelson Tobiasch Florian Peter Busch Jonas Seng Devendra Singh Dhami Kristian Kersting CML 50 0 0 16 Oct 2024
Rethinking Fair Representation Learning for Performance-Sensitive Tasks Charles Jones Fabio De Sousa Ribeiro Mélanie Roschewitz Daniel Coelho De Castro Ben Glocker FaML OOD CML 148 1 0 05 Oct 2024
Learning Causally Invariant Reward Functions from Diverse Demonstrations Ivan Ovinnikov Eugene Bykovets J. M. Buhmann CML 40 0 0 12 Sep 2024
Invariant Correlation of Representation with Label: Enhancing Domain Generalization in Noisy Environments Gaojie Jin Ronghui Mu Xinping Yi Xiaowei Huang Lijun Zhang 67 0 0 01 Jul 2024
Towards a Better Evaluation of Out-of-Domain Generalization Duhun Hwang Suhyun Kang Moonjung Eo Jimyeong Kim Wonjong Rhee 64 0 0 30 May 2024
Targeted Sequential Indirect Experiment Design Elisabeth Ailer Niclas Dern Jason S. Hartford Niki Kilbertus 51 1 0 30 May 2024
Learning Invariant Causal Mechanism from Vision-Language Models Changwen Zheng Siyu Zhao Xingyu Zhang Jiangmeng Li Changwen Zheng Jingyao Wang CML BDL VLM 52 0 0 24 May 2024
Causality Pursuit from Heterogeneous Environments via Neural Adversarial Invariance Learning Yihong Gu Cong Fang Peter Bühlmann Jianqing Fan OOD CML 82 2 0 07 May 2024
Causally Inspired Regularization Enables Domain General Representations Olawale Salaudeen Oluwasanmi Koyejo OOD CML 27 2 0 25 Apr 2024
Invariant Subspace Decomposition Margherita Lazzaretto Jonas Peters Niklas Pfister 26 0 0 15 Apr 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 54 2 0 19 Dec 2023
Invariant Representation via Decoupling Style and Spurious Features from Images Ruimeng Li Yuanhao Pu Zhaoyi Li Hong Xie Defu Lian OOD 33 1 0 11 Dec 2023
Machine-Guided Discovery of a Real-World Rogue Wave Model Dion Häfner Johannes Gemmrich Markus Jochum AI4CE 15 10 0 21 Nov 2023
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? Yongqiang Chen Yatao Bian Kaiwen Zhou Binghui Xie Bo Han James Cheng OOD 45 34 0 29 Oct 2023
Domain Generalisation via Risk Distribution Matching Toan Nguyen Kien Do Bao Duong T. Nguyen OOD 44 4 0 28 Oct 2023
Continual Invariant Risk Minimization Francesco Alesiani Shujian Yu Mathias Niepert OOD 31 1 0 21 Oct 2023
Data Augmentations for Improved (Large) Language Model Generalization Amir Feder Yoav Wald Claudia Shi Suchi Saria David M. Blei OOD CML 36 7 0 19 Oct 2023
Environment-biased Feature Ranking for Novelty Detection Robustness Stefan Smeu Elena Burceanu Emanuela Haller Andrei Liviu Nicolicioiu OOD 44 0 0 21 Sep 2023
Pareto Invariant Representation Learning for Multimedia Recommendation Shanshan Huang Haoxuan Li Qingsong Li Chunyuan Zheng Li Liu CML 29 12 0 09 Aug 2023
Structural restrictions in local causal discovery: identifying direct causes of a target variable Juraj Bodik V. Chavez-Demoulin CML 38 1 0 29 Jul 2023
AI for Anticipatory Action: Moving Beyond Climate Forecasting Benjamin Q. Huynh M. Kiang AI4CE 32 0 0 28 Jul 2023
Causality-oriented robustness: exploiting general noise interventions Xinwei Shen Peter Buhlmann Armeen Taeb OOD 69 8 0 18 Jul 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity H. Aliee Ferdinand Kapl Soroor Hediyeh-zadeh Fabian J. Theis CML 36 6 0 02 Jul 2023
Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models Zeyu Zhou Ruqi Bai Sean Kulinski Murat Kocaoglu David I. Inouye CML 31 2 0 20 Jun 2023
VIBR: Learning View-Invariant Value Functions for Robust Visual Control Tom Dupuis Jaonary Rabarisoa Q. C. Pham David Filliat 49 0 0 14 Jun 2023
Invariant Causal Set Covering Machines Thibaud Godon Baptiste Bauvin Pascal Germain J. Corbeil Alexandre Drouin CML 29 0 0 07 Jun 2023
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 35 57 0 01 Jun 2023
An Invariant Learning Characterization of Controlled Text Generation Carolina Zheng Claudia Shi Keyon Vafa Amir Feder David M. Blei OOD 40 8 0 31 May 2023
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 PINN AI4Cl AI4CE CML 51 75 0 21 May 2023
SFP: Spurious Feature-targeted Pruning for Out-of-Distribution Generalization Yingchun Wang Jingcai Guo Yi Liu Song Guo Weizhan Zhang Xiangyong Cao Qinghua Zheng AAML OODD 45 11 0 19 May 2023
Consistency Regularization for Domain Generalization with Logit Attribution Matching Han Gao Kaican Li Weiyan Xie Zhi Lin Yongxiang Huang Luning Wang Caleb Chen Cao N. Zhang 18 2 0 13 May 2023
Multi-view Adversarial Discriminator: Mine the Non-causal Factors for Object Detection in Unseen Domains Min Xu Lingyun Qin Weijie Chen Shiliang Pu Lei Zhang OOD 19 29 0 06 Apr 2023
A step towards the applicability of algorithms based on invariant causal learning on observational data Borja Guerrero Santillan CML OOD 19 1 0 05 Apr 2023
Predictive Heterogeneity: Measures and Applications Jiashuo Liu Jiayun Wu Yangqiu Song Peng Cui 40 1 0 01 Apr 2023
Mind the Label Shift of Augmentation-based Graph OOD Generalization Junchi Yu Jian Liang Ran He 34 28 0 27 Mar 2023
Achieving Counterfactual Fairness with Imperfect Structural Causal Model Tri Dung Duong Qian Li Guandong Xu 24 2 0 26 Mar 2023