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Kernel Methods for Causal Functions: Dose, Heterogeneous, and
  Incremental Response Curves

Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves

10 October 2020
Rahul Singh
Liyuan Xu
A. Gretton
    OffRL
ArXivPDFHTML

Papers citing "Kernel Methods for Causal Functions: Dose, Heterogeneous, and Incremental Response Curves"

7 / 7 papers shown
Title
Moments of Causal Effects
Moments of Causal Effects
Yuta Kawakami
Jin Tian
CML
41
0
0
08 May 2025
A Dictionary of Closed-Form Kernel Mean Embeddings
A Dictionary of Closed-Form Kernel Mean Embeddings
F. Briol
A. Gessner
Toni Karvonen
Maren Mahsereci
BDL
73
1
0
26 Apr 2025
Spectral Representations for Accurate Causal Uncertainty Quantification
  with Gaussian Processes
Spectral Representations for Accurate Causal Uncertainty Quantification with Gaussian Processes
Hugh Dance
Peter Orbanz
Arthur Gretton
CML
24
1
0
18 Oct 2024
Automatic debiasing of neural networks via moment-constrained learning
Automatic debiasing of neural networks via moment-constrained learning
Christian L. Hines
Oliver J. Hines
CML
OOD
31
0
0
29 Sep 2024
Kernel-based off-policy estimation without overlap: Instance optimality
  beyond semiparametric efficiency
Kernel-based off-policy estimation without overlap: Instance optimality beyond semiparametric efficiency
Wenlong Mou
Peng Ding
Martin J. Wainwright
Peter L. Bartlett
OffRL
11
10
0
16 Jan 2023
Minimax Optimal Kernel Operator Learning via Multilevel Training
Minimax Optimal Kernel Operator Learning via Multilevel Training
Jikai Jin
Yiping Lu
Jose H. Blanchet
Lexing Ying
18
11
0
28 Sep 2022
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves
Rahul Singh
Liyuan Xu
A. Gretton
32
3
0
06 Nov 2021
1