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Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment
  Restriction
v1v2v3v4v5v6v7 (latest)

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
ArXiv (abs)PDFHTML

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
Adjustment for Confounding using Pre-Trained Representations
Rickmer Schulte
David Rügamer
Thomas Nagler
CMLBDL
27
0
0
17 Jun 2025
DeCaFlow: A Deconfounding Causal Generative Model
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
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
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
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
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
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
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
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
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
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
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
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
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
Towards Principled Causal Effect Estimation by Deep Identifiable Models
Pengzhou (Abel) Wu
Kenji Fukumizu
BDLOODCML
72
3
0
30 Sep 2021
Proximal Causal Inference for Complex Longitudinal Studies
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
Quasi-Bayesian Dual Instrumental Variable Regression
Ziyun Wang
Yuhao Zhou
Zhaolin Ren
Jun Zhu
63
2
0
16 Jun 2021
Causal Effect Inference for Structured Treatments
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
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
Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments
Rahul Singh
CML
98
41
0
18 Dec 2020
Semiparametric proximal causal inference
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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