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Learning individual-level causal effects from observational data, such as inferring the most effective medication for a specific patient, is a problem of growing importance for policy makers.
A note on the use of proxy variables
M. R. Wickens · 1972
Earlier work this paper cites.
Exploratory latent structure analysis using both identifiable and unidentifiable models
L. A. Goodman · 1974
Earlier work this paper cites.
More factors than subjects, tests and treatments: an indeterminacy theorem for canonical decomposition and individual differences scaling
J. B. Kruskal · 1976
Earlier work this paper cites.
Proxy variables and specification bias
P. A. Frost · 1979
Earlier work this paper cites.
Correcting for misclassification in two-way tables and matched-pair studies
S. Greenland and D. G. Kleinbaum · 1983
Earlier work this paper cites.
Errors in variables in panel data
Z. Griliches and J. A. Hausman · 1986
Earlier work this paper cites.
Evaluating the econometric evaluations of training programs with experimental data
R. J. LaLonde · 1986
Earlier work this paper cites.
Adjusting for errors in classification and measurement in the analysis of partly and purely categorical data
J. Selén · 1986
Earlier work this paper cites.
Measurement error models
W. Fuller · 1987
Earlier work this paper cites.
Introduction to econometrics , volume 2
G. S. Maddala and K. Lahiri · 1992
Earlier work this paper cites.
Learning mixtures of dag models
B. Thiesson, C. Meek, D. M. Chickering, and D. Heckerman · 1998
Earlier work this paper cites.
Measuring living standards with proxy variables
M. R. Montgomery, M. Gragnolati, K. A. Burke, and E. Paredes · 2000
Earlier work this paper cites.
Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of india
D. Filmer and L. H. Pritchett · 2001
Earlier work this paper cites.
The costs of low birth weight
D. Almond, K. Y. Chay, and D. S. Lee · 2005
Earlier work this paper cites.
Learning mixtures of separated nonspherical gaussians
S. Arora and R. Kannan · 2005
Earlier work this paper cites.
Does matching overcome lalonde’s critique of nonexperimental estimators?
J. A. Smith and P. E. Todd · 2005
Earlier work this paper cites.
Mostly harmless econometrics: An empiricist’s companion
J. D. Angrist and J.-S. Pischke · 2008
Earlier work this paper cites.
On identifying total effects in the presence of latent variables and selection bias
Z. Cai and M. Kuroki · 2008
Earlier work this paper cites.
Bias analysis
S. Greenland and T. Lash · 2008
Earlier work this paper cites.
Identifiability of parameters in latent structure models with many observed variables
E. S. Allman, C. Matias, and J. A. Rhodes · 2009
Cited alongside, same era.
Socioeconomic status measurement with discrete proxy variables: Is principal component analysis a reliable answer?
S. Kolenikov and G. Angeles · 2009
Cited alongside, same era.
Causality
J. Pearl · 2009
Cited alongside, same era.
On estimating firm-level production functions using proxy variables to control for unobservables
J. M. Wooldridge · 2009
Cited alongside, same era.
Bayesian nonparametric modeling for causal inference
J. L. Hill · 2011
Cited alongside, same era.
Measurement bias and effect restoration in causal inference
M. Kuroki and J. Pearl · 2011
Cited alongside, same era.
DRAW: A Recurrent Neural Network For Image Generation
K. Gregor, I. Danihelka, A. Graves, D. Jimenez Rezende, and D. Wierstra · 2015
Later among the works it cites.
Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2015
Later among the works it cites.
Detecting latent heterogeneity
J. Pearl · 2015
Later among the works it cites.
Variational inference with normalizing flows
D. J. Rezende and S. Mohamed · 2015
Later among the works it cites.
The variational Gaussian process
D. Tran, R. Ranganath, and D. M. Blei · 2015
Later among the works it cites.
Estimation and inference of heterogeneous treatment effects using random forests
S. Wager and S. Athey · 2015
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D. Hsu, S. M. Kakade, and T. Zhang · 2012
Cited alongside, same era.
On measurement bias in causal inference
J. Pearl · 2012
Cited alongside, same era.
Discovering hidden variables in noisy-or networks using quartet tests
Y. Jernite, Y. Halpern, and D. Sontag · 2013
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Tensor decompositions for learning latent variable models
A. Anandkumar, R. Ge, D. J. Hsu, S. M. Kakade, and M. Telgarsky · 2014
Cited alongside, same era.
Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2014
Cited alongside, same era.
Later among the works it cites.
Tensorflow: Large-scale machine learning on heterogeneous distributed systems
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Later among the works it cites.
Provable learning of noisy-or networks
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Later among the works it cites.
Unsupervised Learning of 3D Structure from Images
D. Jimenez Rezende, S. M. A. Eslami, S. Mohamed, P. Battaglia, M. Jaderberg, and N. Heess · 2016
Later among the works it cites.
Learning representations for counterfactual inference
F. D. Johansson, U. Shalit, and D. Sontag · 2016
Later among the works it cites.
Improving variational inference with inverse autoregressive flow
D. P. Kingma, T. Salimans, and M. Welling · 2016
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The variational fair autoencoder
C. Louizos, K. Swersky, Y. Li, M. Welling, and R. Zemel · 2016
Later among the works it cites.
Auxiliary deep generative models
L. Maaløe, C. K. Sønderby, S. K. Sønderby, and O. Winther · 2016
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Identifying causal effects with proxy variables of an unmeasured confounder
W. Miao, Z. Geng, and E. Tchetgen Tchetgen · 2016
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Combining observational and experimental data to find heterogeneous treatment effects
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Operator variational inference
R. Ranganath, D. Tran, J. Altosaar, and D. Blei · 2016
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Estimating individual treatment effect: generalization bounds and algorithms
U. Shalit, F. Johansson, and D. Sontag · 2016
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Edward: A library for probabilistic modeling, inference, and criticism
D. Tran, A. Kucukelbir, A. B. Dieng, M. Rudolph, D. Liang, and D. M. Blei · 2016
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