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Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction
10 May 2021
Afsaneh Mastouri
Yuchen Zhu
Limor Gultchin
Anna Korba
Ricardo M. A. Silva
Matt J. Kusner
Arthur Gretton
Krikamol Muandet
CML
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Papers citing
"Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction"
21 / 21 papers shown
Title
Adjustment for Confounding using Pre-Trained Representations
Rickmer Schulte
David Rügamer
Thomas Nagler
CML
BDL
27
0
0
17 Jun 2025
DeCaFlow: A Deconfounding Causal Generative Model
Alejandro Almodóvar
Adrián Javaloy
J. Parras
Santiago Zazo
Isabel Valera
CML
78
0
0
19 Mar 2025
Spectral Representation for Causal Estimation with Hidden Confounders
Zhaolin Ren
Haotian Sun
Antoine Moulin
Arthur Gretton
Bo Dai
CML
127
3
0
15 Jul 2024
Kernel Single Proxy Control for Deterministic Confounding
Liyuan Xu
Arthur Gretton
CML
87
3
0
08 Aug 2023
Causal Discovery via Conditional Independence Testing with Proxy Variables
Mingzhou Liu
Xinwei Sun
Yu Qiao
Yizhou Wang
CML
59
2
0
09 May 2023
Optimal Treatment Regimes for Proximal Causal Learning
Tao Shen
Yifan Cui
CML
70
3
0
19 Dec 2022
Spectral Representation Learning for Conditional Moment Models
Ziyu Wang
Yucen Luo
Yueru Li
Jun Zhu
Bernhard Schölkopf
CML
99
9
0
29 Oct 2022
Inference on Strongly Identified Functionals of Weakly Identified Functions
Andrew Bennett
Nathan Kallus
Xiaojie Mao
Whitney Newey
Vasilis Syrgkanis
Masatoshi Uehara
114
17
0
17 Aug 2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems
Masatoshi Uehara
Ayush Sekhari
Jason D. Lee
Nathan Kallus
Wen Sun
OffRL
101
36
0
24 Jun 2022
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
Miao Lu
Yifei Min
Zhaoran Wang
Zhuoran Yang
OffRL
106
23
0
26 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
92
14
0
19 May 2022
Long-term Causal Inference Under Persistent Confounding via Data Combination
Guido Imbens
Nathan Kallus
Xiaojie Mao
Yuhao Wang
CML
119
49
0
15 Feb 2022
Multi-treatment Effect Estimation from Biomedical Data
Raquel Y. S. Aoki
Yizhou Chen
M. Ester
68
0
0
14 Dec 2021
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes
C. Shi
Masatoshi Uehara
Jiawei Huang
Nan Jiang
OffRL
101
26
0
12 Nov 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models
Pengzhou (Abel) Wu
Kenji Fukumizu
BDL
OOD
CML
72
3
0
30 Sep 2021
Proximal Causal Inference for Complex Longitudinal Studies
Andrew Ying
Wang Miao
Xu Shi
E. T. Tchetgen
125
40
0
15 Sep 2021
Quasi-Bayesian Dual Instrumental Variable Regression
Ziyun Wang
Yuhao Zhou
Zhaolin Ren
Jun Zhu
65
2
0
16 Jun 2021
Causal Effect Inference for Structured Treatments
Jean Kaddour
Yuchen Zhu
Qi Liu
Matt J. Kusner
Ricardo M. A. Silva
CML
262
51
0
03 Jun 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
94
44
0
07 Apr 2021
Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments
Rahul Singh
CML
98
41
0
18 Dec 2020
Semiparametric proximal causal inference
Yifan Cui
Hongming Pu
Xu Shi
Wang Miao
E. T. Tchetgen Tchetgen
80
108
0
17 Nov 2020
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