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Bayesian Nonparametric Causal Inference: Information Rates and Learning
  Algorithms
v1v2 (latest)

Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms

24 December 2017
Ahmed Alaa
Mihaela van der Schaar
    CML
ArXiv (abs)PDFHTML

Papers citing "Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms"

11 / 11 papers shown
Title
SOReL and TOReL: Two Methods for Fully Offline Reinforcement Learning
SOReL and TOReL: Two Methods for Fully Offline Reinforcement Learning
Mattie Fellows
Clarisse Wibault
Uljad Berdica
Johannes Forkel
Jakob Foerster
Michael A. Osborne
OffRLOnRL
58
0
0
28 May 2025
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
Valentyn Melnychuk
Stefan Feuerriegel
Mihaela van der Schaar
CML
272
5
0
05 Nov 2024
New User Event Prediction Through the Lens of Causal Inference
New User Event Prediction Through the Lens of Causal Inference
H. Yuchi
Shixiang Zhu
Li Dong
Yigit M. Arisoy
Matthew C. Spencer
91
0
0
08 Jul 2024
Bounds on Representation-Induced Confounding Bias for Treatment Effect
  Estimation
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
CML
79
10
0
19 Nov 2023
Causal Transformer for Estimating Counterfactual Outcomes
Causal Transformer for Estimating Counterfactual Outcomes
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
CML
107
99
0
14 Apr 2022
Conditional Distributional Treatment Effect with Kernel Conditional Mean
  Embeddings and U-Statistic Regression
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression
Junhyung Park
Uri Shalit
Bernhard Schölkopf
Krikamol Muandet
CML
104
33
0
16 Feb 2021
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory
  to Learning Algorithms
Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
Alicia Curth
M. Schaar
CML
181
149
0
26 Jan 2021
Causal Inference using Gaussian Processes with Structured Latent
  Confounders
Causal Inference using Gaussian Processes with Structured Latent Confounders
Sam Witty
Kenta Takatsu
David D. Jensen
Vikash K. Mansinghka
CML
140
19
0
14 Jul 2020
Deconfounding Reinforcement Learning in Observational Settings
Deconfounding Reinforcement Learning in Observational Settings
Chaochao Lu
Bernhard Schölkopf
José Miguel Hernández-Lobato
CMLOOD
173
75
0
26 Dec 2018
Counterfactual Normalization: Proactively Addressing Dataset Shift and
  Improving Reliability Using Causal Mechanisms
Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms
Adarsh Subbaswamy
Suchi Saria
OOD
62
25
0
09 Aug 2018
Variable Prioritization in Nonlinear Black Box Methods: A Genetic
  Association Case Study
Variable Prioritization in Nonlinear Black Box Methods: A Genetic Association Case Study
Lorin Crawford
Seth R. Flaxman
D. Runcie
M. West
47
28
0
22 Jan 2018
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