Kernel Instrumental Variable Regression

1 June 2019

Papers citing "Kernel Instrumental Variable Regression"

50 / 110 papers shown

Title
A Dictionary of Closed-Form Kernel Mean Embeddings F. Briol A. Gessner Toni Karvonen Maren Mahsereci BDL 78 1 0 26 Apr 2025
A Unifying Framework for Causal Imitation Learning with Hidden Confounders Daqian Shao Thomas Kleine Buening Marta Z. Kwiatkowska CML 71 1 0 11 Feb 2025
Achievable distributional robustness when the robust risk is only partially identified Julia Kostin Nicola Gnecco Fanny Yang 73 3 0 04 Feb 2025
Testability of Instrumental Variables in Additive Nonlinear, Non-Constant Effects Models Xichen Guo Zheng Li Erdun Gao Yan Zeng Zhi Geng Feng Xie 65 0 0 19 Nov 2024
An Overview of Causal Inference using Kernel Embeddings Dino Sejdinovic CML BDL 35 2 0 30 Oct 2024
Learning Representations of Instruments for Partial Identification of Treatment Effects J. Schweisthal Dennis Frauen Maresa Schröder Konstantin Hess Niki Kilbertus Stefan Feuerriegel CML 34 1 0 11 Oct 2024
Transformers Handle Endogeneity in In-Context Linear Regression Haodong Liang Krishnakumar Balasubramanian Lifeng Lai 41 1 0 02 Oct 2024
Causal Effect Estimation using identifiable Variational AutoEncoder with Latent Confounders and Post-Treatment Variables Yang Xie Ziqi Xu Debo Cheng Jiuyong Li Lin Liu Yinghao Zhang Zaiwen Feng CML BDL 26 0 0 13 Aug 2024
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression Anpeng Wu Kun Kuang Ruoxuan Xiong Xiangwei Chen Zexu Sun Fei Wu Kun Zhang CML 27 0 0 10 Aug 2024
Causal Inference with Complex Treatments: A Survey Yingrong Wang Haoxuan Li Minqin Zhu Anpeng Wu Ruoxuan Xiong Fei Wu Kun Kuang CML 48 1 0 19 Jul 2024
Spectral Representation for Causal Estimation with Hidden Confounders Tongzheng Ren Haotian Sun Antoine Moulin Arthur Gretton Bo Dai CML 32 1 0 15 Jul 2024
Nonparametric Jackknife Instrumental Variable Estimation and Confounding Robust Surrogate Indices Aurélien F. Bibaut Nathan Kallus Apoorva Lal CML 38 0 0 20 Jun 2024
Causal Inference with Latent Variables: Recent Advances and Future Prospectives Yaochen Zhu Yinhan He Jing Ma Mengxuan Hu Sheng Li Jundong Li CML 43 3 0 20 Jun 2024
Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data M. Oprescu Nathan Kallus CML 28 0 0 10 Jun 2024
Self-Distilled Disentangled Learning for Counterfactual Prediction Xinshu Li Mingming Gong Lina Yao CML 35 2 0 09 Jun 2024
Probabilities of Causation for Continuous and Vector Variables Yuta Kawakami Manabu Kuroki Jin Tian 27 4 0 30 May 2024
Targeted Sequential Indirect Experiment Design Elisabeth Ailer Niclas Dern Jason S. Hartford Niki Kilbertus 46 1 0 30 May 2024
Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data Xuxing Chen Abhishek Roy Yifan Hu Krishnakumar Balasubramanian 43 1 0 29 May 2024
Optimal Rates for Vector-Valued Spectral Regularization Learning Algorithms Dimitri Meunier Zikai Shen Mattes Mollenhauer Arthur Gretton Zhu Li 43 4 0 23 May 2024
Geometry-Aware Instrumental Variable Regression Heiner Kremer Bernhard Schölkopf 46 0 0 19 May 2024
A Functional Model Method for Nonconvex Nonsmooth Conditional Stochastic Optimization Andrzej Ruszczyñski Shangzhe Yang 29 0 0 17 May 2024
Learning Decision Policies with Instrumental Variables through Double Machine Learning Daqian Shao Ashkan Soleymani Francesco Quinzan Marta Z. Kwiatkowska 39 1 0 14 May 2024
Bounding Causal Effects with Leaky Instruments David S. Watson Jordan Penn L. Gunderson Gecia Bravo Hermsdorff Afsaneh Mastouri Ricardo M. A. Silva CML 29 1 0 05 Apr 2024
Functional Bilevel Optimization for Machine Learning Ieva Petrulionyte Julien Mairal Michael Arbel 51 2 0 29 Mar 2024
Neural-Kernel Conditional Mean Embeddings Eiki Shimizu Kenji Fukumizu Dino Sejdinovic 43 3 0 16 Mar 2024
Proxy Methods for Domain Adaptation Katherine Tsai Stephen R. Pfohl Olawale Salaudeen Nicole Chiou Matt J. Kusner Alexander DÁmour Oluwasanmi Koyejo Arthur Gretton OOD 35 2 0 12 Mar 2024
Asymptotic Theory for Linear Functionals of Kernel Ridge Regression Rui Tuo Lu Zou 21 0 0 07 Mar 2024
Regularized DeepIV with Model Selection Zihao Li Hui Lan Vasilis Syrgkanis Mengdi Wang Masatoshi Uehara 38 2 0 07 Mar 2024
Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients Yuri S. Fonseca Caio Peixoto Yuri F. Saporito 42 2 0 08 Feb 2024
Towards Optimal Sobolev Norm Rates for the Vector-Valued Regularized Least-Squares Algorithm Zhu Li Dimitri Meunier Mattes Mollenhauer Arthur Gretton 31 5 0 12 Dec 2023
Counterfactual Prediction Under Selective Confounding Sohaib Kiani Jared Barton Jon Sushinsky Lynda Heimbach Bo Luo CML 19 1 0 21 Oct 2023
Federated Conditional Stochastic Optimization Xidong Wu Jianhui Sun Zhengmian Hu Junyi Li Aidong Zhang Heng-Chiao Huang FedML 44 4 0 04 Oct 2023
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder Ziqi Xu Debo Cheng Jiuyong Li Jixue Liu Lin Liu Kui Yu CML 39 9 0 03 Oct 2023
Conditional Instrumental Variable Regression with Representation Learning for Causal Inference Debo Cheng Ziqi Xu Jiuyong Li Lin Liu Jixue Liu T. Le CML 19 6 0 03 Oct 2023
A Convex Framework for Confounding Robust Inference Kei Ishikawa Naio He Takafumi Kanamori OffRL 17 0 0 21 Sep 2023
Causal Strategic Learning with Competitive Selection Kiet Q. H. Vo Muneeb Aadil Siu Lun Chau Krikamol Muandet CML 19 2 0 30 Aug 2023
Source Condition Double Robust Inference on Functionals of Inverse Problems Andrew Bennett Nathan Kallus Xiaojie Mao Whitney Newey Vasilis Syrgkanis Masatoshi Uehara 29 5 0 25 Jul 2023
Approximate Causal Effect Identification under Weak Confounding Ziwei Jiang Lai Wei Murat Kocaoglu CML 25 0 0 22 Jun 2023
Sharp Bounds for Generalized Causal Sensitivity Analysis Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel CML 35 18 0 26 May 2023
An Efficient Doubly-Robust Test for the Kernel Treatment Effect Diego Martinez-Taboada Aaditya Ramdas Edward H. Kennedy OOD 26 5 0 26 Apr 2023
Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion Ziqi Xu Debo Cheng Jiuyong Li Jixue Liu Lin Liu Kui Yu CML 29 2 0 24 Apr 2023
Debiasing Conditional Stochastic Optimization Lie He S. Kasiviswanathan CML BDL 52 4 0 20 Apr 2023
A Unified Framework of Policy Learning for Contextual Bandit with Confounding Bias and Missing Observations Siyu Chen Yitan Wang Zhaoran Wang Zhuoran Yang OffRL 36 2 0 20 Mar 2023
Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression Junho Kim Byung-Kwan Lee Yonghyun Ro CML AAML 25 18 0 02 Mar 2023
Kernel Conditional Moment Constraints for Confounding Robust Inference Kei Ishikawa Niao He OffRL 25 3 0 26 Feb 2023
Sequential Underspecified Instrument Selection for Cause-Effect Estimation Elisabeth Ailer Jason S. Hartford Niki Kilbertus CML 22 3 0 11 Feb 2023
Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness Andrew Bennett Nathan Kallus Xiaojie Mao Whitney Newey Vasilis Syrgkanis Masatoshi Uehara 33 14 0 10 Feb 2023
An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models Yufeng Zhang Boyi Liu Qi Cai Lingxiao Wang Zhaoran Wang 53 11 0 30 Dec 2022
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
Causal Inference with Conditional Instruments using Deep Generative Models Debo Cheng Ziqi Xu Jiuyong Li Lin Liu Jixue Liu T. Le CML 29 11 0 29 Nov 2022