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Spectral Representation for Causal Estimation with Hidden Confounders

Spectral Representation for Causal Estimation with Hidden Confounders

15 July 2024
Tongzheng Ren
Haotian Sun
Antoine Moulin
Arthur Gretton
Bo Dai
    CML
ArXivPDFHTML

Papers citing "Spectral Representation for Causal Estimation with Hidden Confounders"

24 / 24 papers shown
Title
Representation Learning via Non-Contrastive Mutual Information
Representation Learning via Non-Contrastive Mutual Information
Z. Guo
Bernardo Avila-Pires
Khimya Khetarpal
Dale Schuurmans
Bo Dai
SSL
102
0
0
23 Apr 2025
Regularized DeepIV with Model Selection
Regularized DeepIV with Model Selection
Zihao Li
Hui Lan
Vasilis Syrgkanis
Mengdi Wang
Masatoshi Uehara
74
2
0
07 Mar 2024
Source Condition Double Robust Inference on Functionals of Inverse
  Problems
Source Condition Double Robust Inference on Functionals of Inverse Problems
Andrew Bennett
Nathan Kallus
Xiaojie Mao
Whitney Newey
Vasilis Syrgkanis
Masatoshi Uehara
62
5
0
25 Jul 2023
Minimax Instrumental Variable Regression and $L_2$ Convergence
  Guarantees without Identification or Closedness
Minimax Instrumental Variable Regression and L2L_2L2​ Convergence Guarantees without Identification or Closedness
Andrew Bennett
Nathan Kallus
Xiaojie Mao
Whitney Newey
Vasilis Syrgkanis
Masatoshi Uehara
57
14
0
10 Feb 2023
Latent Variable Representation for Reinforcement Learning
Latent Variable Representation for Reinforcement Learning
Tongzheng Ren
Chenjun Xiao
Tianjun Zhang
Na Li
Zhaoran Wang
Sujay Sanghavi
Dale Schuurmans
Bo Dai
OffRL
55
10
0
17 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
59
7
0
29 Oct 2022
Spectral Decomposition Representation for Reinforcement Learning
Spectral Decomposition Representation for Reinforcement Learning
Tongzheng Ren
Tianjun Zhang
Lisa Lee
Joseph E. Gonzalez
Dale Schuurmans
Bo Dai
OffRL
58
27
0
19 Aug 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
62
16
0
17 Aug 2022
Optimal Rates for Regularized Conditional Mean Embedding Learning
Optimal Rates for Regularized Conditional Mean Embedding Learning
Zhu Li
Dimitri Meunier
Mattes Mollenhauer
Arthur Gretton
47
49
0
02 Aug 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning
  in Online Reinforcement Learning
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning
Shuang Qiu
Lingxiao Wang
Chenjia Bai
Zhuoran Yang
Zhaoran Wang
SSL
OffRL
59
32
0
29 Jul 2022
Making Linear MDPs Practical via Contrastive Representation Learning
Making Linear MDPs Practical via Contrastive Representation Learning
Tianjun Zhang
Tongzheng Ren
Mengjiao Yang
Joseph E. Gonzalez
Dale Schuurmans
Bo Dai
42
44
0
14 Jul 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
55
14
0
19 May 2022
Deep Proxy Causal Learning and its Application to Confounded Bandit
  Policy Evaluation
Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation
Liyuan Xu
Heishiro Kanagawa
Arthur Gretton
CML
33
36
0
07 Jun 2021
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment
  Restriction
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
29
61
0
10 May 2021
Instrumental Variable Regression via Kernel Maximum Moment Loss
Instrumental Variable Regression via Kernel Maximum Moment Loss
Rui Zhang
Masaaki Imaizumi
Bernhard Schölkopf
Krikamol Muandet
23
7
0
15 Oct 2020
Learning Deep Features in Instrumental Variable Regression
Learning Deep Features in Instrumental Variable Regression
Liyuan Xu
Yutian Chen
Siddarth Srinivasan
Nando de Freitas
Arnaud Doucet
Arthur Gretton
CML
OOD
54
68
0
14 Oct 2020
Provably Efficient Neural Estimation of Structural Equation Model: An
  Adversarial Approach
Provably Efficient Neural Estimation of Structural Equation Model: An Adversarial Approach
Luofeng Liao
You-Lin Chen
Zhuoran Yang
Bo Dai
Zhaoran Wang
Mladen Kolar
70
33
0
02 Jul 2020
Minimax Estimation of Conditional Moment Models
Minimax Estimation of Conditional Moment Models
Nishanth Dikkala
Greg Lewis
Lester W. Mackey
Vasilis Syrgkanis
123
100
0
12 Jun 2020
Provably Efficient Reinforcement Learning with Linear Function
  Approximation
Provably Efficient Reinforcement Learning with Linear Function Approximation
Chi Jin
Zhuoran Yang
Zhaoran Wang
Michael I. Jordan
76
549
0
11 Jul 2019
Kernel Instrumental Variable Regression
Kernel Instrumental Variable Regression
Rahul Singh
M. Sahani
Arthur Gretton
74
172
0
01 Jun 2019
Deep Generalized Method of Moments for Instrumental Variable Analysis
Deep Generalized Method of Moments for Instrumental Variable Analysis
Andrew Bennett
Nathan Kallus
Tobias Schnabel
48
125
0
29 May 2019
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and
  Regret Bound
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
Lin F. Yang
Mengdi Wang
OffRL
GP
50
284
0
24 May 2019
Causal Effect Inference with Deep Latent-Variable Models
Causal Effect Inference with Deep Latent-Variable Models
Christos Louizos
Uri Shalit
Joris Mooij
David Sontag
R. Zemel
Max Welling
CML
BDL
148
739
0
24 May 2017
Conditional mean embeddings as regressors - supplementary
Conditional mean embeddings as regressors - supplementary
Steffen Grunewalder
Guy Lever
Luca Baldassarre
Sam Patterson
Arthur Gretton
Massimiliano Pontil
102
144
0
21 May 2012
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