Kernel Instrumental Variable Regression

1 June 2019

Papers citing "Kernel Instrumental Variable Regression"

50 / 110 papers shown

Title
Confounder Balancing for Instrumental Variable Regression with Latent Variable Anpeng Wu Kun Kuang Ruoxuan Xiong Bo Li Fei Wu CML 40 0 0 18 Nov 2022
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation Diego Martinez-Taboada Dino Sejdinovic CML OffRL 23 0 0 02 Nov 2022
Nonlinear Causal Discovery via Kernel Anchor Regression Wenqi Shi Wenkai Xu CML BDL 27 0 0 30 Oct 2022
Spectral Representation Learning for Conditional Moment Models Ziyu Wang Yucen Luo Yueru Li Jun Zhu Bernhard Schölkopf CML 36 7 0 29 Oct 2022
Minimax Optimal Kernel Operator Learning via Multilevel Training Jikai Jin Yiping Lu Jose H. Blanchet Lexing Ying 26 12 0 28 Sep 2022
Dual Instrumental Method for Confounded Kernelized Bandits Xueping Gong Jiheng Zhang 14 1 0 07 Sep 2022
Learning Instrumental Variable from Data Fusion for Treatment Effect Estimation Anpeng Wu Kun Kuang Ruoxuan Xiong Minqing Zhu Yuxuan Liu Bo Li Furui Liu Zhihua Wang Fei Wu CML 33 7 0 23 Aug 2022
Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey Debo Cheng Jiuyong Li Lin Liu Jixue Liu T. Le CML 41 29 0 20 Aug 2022
Estimating individual treatment effects under unobserved confounding using binary instruments Dennis Frauen Stefan Feuerriegel CML 23 18 0 17 Aug 2022
Inference on Strongly Identified Functionals of Weakly Identified Functions Andrew Bennett Nathan Kallus Xiaojie Mao Whitney Newey Vasilis Syrgkanis Masatoshi Uehara 38 15 0 17 Aug 2022
Optimal Rates for Regularized Conditional Mean Embedding Learning Zhu Li Dimitri Meunier Mattes Mollenhauer Arthur Gretton 30 47 0 02 Aug 2022
Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach Yuchen Zhu Limor Gultchin Arthur Gretton Matt J. Kusner Ricardo M. A. Silva CML 13 15 0 18 Jun 2022
Constructing unbiased gradient estimators with finite variance for conditional stochastic optimization T. Goda Wataru Kitade 8 3 0 04 Jun 2022
Indirect Active Learning Shashank Singh 18 0 0 03 Jun 2022
Fast Instrument Learning with Faster Rates Ziyu Wang Yuhao Zhou Jun Zhu 29 3 0 22 May 2022
Deep Learning Methods for Proximal Inference via Maximum Moment Restriction Benjamin Kompa David R. Bellamy Thomas Kolokotrones J. M. Robins Andrew L. Beam 39 12 0 19 May 2022
Identifiability of Sparse Causal Effects using Instrumental Variables Niklas Pfister J. Peters CML 8 9 0 17 Mar 2022
Stochastic Causal Programming for Bounding Treatment Effects Kirtan Padh Jakob Zeitler David S. Watson Matt J. Kusner Ricardo M. A. Silva Niki Kilbertus CML 32 26 0 22 Feb 2022
Long-term Causal Inference Under Persistent Confounding via Data Combination Guido Imbens Nathan Kallus Xiaojie Mao Yuhao Wang CML 32 44 0 15 Feb 2022
Towards Empirical Process Theory for Vector-Valued Functions: Metric Entropy of Smooth Function Classes Junhyung Park Krikamol Muandet 27 6 0 09 Feb 2022
Importance Weighting Approach in Kernel Bayes' Rule Liyuan Xu Yutian Chen Arnaud Doucet Arthur Gretton 12 1 0 05 Feb 2022
Exploiting Independent Instruments: Identification and Distribution Generalization Sorawit Saengkyongam Leonard Henckel Niklas Pfister J. Peters 16 18 0 03 Feb 2022
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation Yi-Fan Zhang Hanlin Zhang Zachary Chase Lipton Li Erran Li Eric P. Xing OODD 26 29 0 02 Feb 2022
Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection Rahul Singh 26 1 0 09 Nov 2021
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves Rahul Singh Liyuan Xu Arthur Gretton 32 3 0 06 Nov 2021
Instrumental Variable-Driven Domain Generalization with Unobserved Confounders Junkun Yuan Xu Ma Ruoxuan Xiong Biwei Huang Xiangyu Liu Fei Wu Lanfen Lin Kun Kuang OOD CML 20 12 0 04 Oct 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 30 3 0 30 Sep 2021
Kernel PCA with the Nyström method Fredrik Hallgren 18 1 0 12 Sep 2021
Learning Causal Models from Conditional Moment Restrictions by Importance Weighting Masahiro Kato Masaaki Imaizumi K. McAlinn Haruo Kakehi Shota Yasui CML 47 5 0 03 Aug 2021
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition Junkun Yuan Anpeng Wu Kun Kuang Yangqiu Song Runze Wu Fei Wu Lanfen Lin CML 47 38 0 13 Jul 2021
Quasi-Bayesian Dual Instrumental Variable Regression Ziyun Wang Yuhao Zhou Tongzheng Ren Jun Zhu 22 2 0 16 Jun 2021
Operationalizing Complex Causes: A Pragmatic View of Mediation Limor Gultchin David S. Watson Matt J. Kusner Ricardo M. A. Silva CML 17 5 0 09 Jun 2021
Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation Liyuan Xu Heishiro Kanagawa Arthur Gretton CML 23 35 0 07 Jun 2021
BayesIMP: Uncertainty Quantification for Causal Data Fusion Siu Lun Chau Jean-François Ton Javier I. González Yee Whye Teh Dino Sejdinovic CML 14 18 0 07 Jun 2021
Instrument Space Selection for Kernel Maximum Moment Restriction Rui Zhang Krikamol Muandet Bernhard Schölkopf Masaaki Imaizumi 30 3 0 07 Jun 2021
Causal Effect Inference for Structured Treatments Jean Kaddour Yuchen Zhu Qi Liu Matt J. Kusner Ricardo M. A. Silva CML 182 50 0 03 Jun 2021
A Simple and General Debiased Machine Learning Theorem with Finite Sample Guarantees Victor Chernozhukov Whitney Newey Rahul Singh FedML 20 24 0 31 May 2021
Deconditional Downscaling with Gaussian Processes Siu Lun Chau S. Bouabid Dino Sejdinovic BDL 16 21 0 27 May 2021
On Instrumental Variable Regression for Deep Offline Policy Evaluation Yutian Chen Liyuan Xu Çağlar Gülçehre T. Paine Arthur Gretton Nando de Freitas Arnaud Doucet OffRL 51 18 0 21 May 2021
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction Afsaneh Mastouri Yuchen Zhu Limor Gultchin Anna Korba Ricardo M. A. Silva Matt J. Kusner Arthur Gretton Krikamol Muandet CML 19 59 0 10 May 2021
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference AmirEmad Ghassami Andrew Ying I. Shpitser E. T. Tchetgen 21 43 0 07 Apr 2021
Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach Nathan Kallus Xiaojie Mao Masatoshi Uehara CML 27 66 0 25 Mar 2021
Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning Luofeng Liao Zuyue Fu Zhuoran Yang Yixin Wang Mladen Kolar Zhaoran Wang OffRL 18 34 0 19 Feb 2021
Causal Gradient Boosting: Boosted Instrumental Variable Regression Edvard Bakhitov Amandeep Singh 9 12 0 15 Jan 2021
Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments Rahul Singh CML 31 39 0 18 Dec 2020
Regularised Least-Squares Regression with Infinite-Dimensional Output Space Junhyunng Park Krikamol Muandet 11 8 0 21 Oct 2020
Instrumental Variable Regression via Kernel Maximum Moment Loss Rui Zhang Masaaki Imaizumi Bernhard Schölkopf Krikamol Muandet 6 7 0 15 Oct 2020
Learning Deep Features in Instrumental Variable Regression Liyuan Xu Yutian Chen Siddarth Srinivasan Nando de Freitas Arnaud Doucet Arthur Gretton CML OOD 28 68 0 14 Oct 2020
Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves Rahul Singh Liyuan Xu Arthur Gretton OffRL 63 27 0 10 Oct 2020
Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach Luofeng Liao You-Lin Chen Zhuoran Yang Bo Dai Zhaoran Wang Mladen Kolar 30 33 0 02 Jul 2020