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Counterfactual Prediction with Deep Instrumental Variables Networks

Counterfactual Prediction with Deep Instrumental Variables Networks

30 December 2016
Jason S. Hartford
Greg Lewis
Kevin Leyton-Brown
Matt Taddy
    CML
    OOD
ArXivPDFHTML

Papers citing "Counterfactual Prediction with Deep Instrumental Variables Networks"

8 / 8 papers shown
Title
Deep Multi-Modal Structural Equations For Causal Effect Estimation With
  Unstructured Proxies
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies
Shachi Deshpande
Kaiwen Wang
Dhruv Sreenivas
Zheng Li
Volodymyr Kuleshov
CML
SyDa
10
11
0
18 Mar 2022
A framework for massive scale personalized promotion
A framework for massive scale personalized promotion
Yitao Shen
Yue Wang
Xingyu Lu
Feng Qi
Jia Yan
Yixiang Mu
Yao Yang
YiFan Peng
Jinjie Gu
14
3
0
27 Aug 2021
Perturbing Inputs to Prevent Model Stealing
Perturbing Inputs to Prevent Model Stealing
J. Grana
AAML
SILM
16
5
0
12 May 2020
Monte Carlo Gradient Estimation in Machine Learning
Monte Carlo Gradient Estimation in Machine Learning
S. Mohamed
Mihaela Rosca
Michael Figurnov
A. Mnih
32
397
0
25 Jun 2019
How to Make Causal Inferences Using Texts
How to Make Causal Inferences Using Texts
Naoki Egami
Christian Fong
Justin Grimmer
Margaret E. Roberts
Brandon M Stewart
CML
26
137
0
06 Feb 2018
Bayesian Inference of Individualized Treatment Effects using Multi-task
  Gaussian Processes
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes
Ahmed Alaa
M. Schaar
CML
33
298
0
10 Apr 2017
Estimation and Inference on Nonlinear and Heterogeneous Effects
Estimation and Inference on Nonlinear and Heterogeneous Effects
Marc Ratkovic
D. Tingley
12
11
0
16 Mar 2017
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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