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Motivated by the rising abundance of observational data with continuous treatments, we investigate the problem of estimating the average dose-response curve (ADRF).
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BN Prichard and PM Gillam · 1971
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Varying-coefficient models
Trevor Hastie and Robert Tibshirani · 1993
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Dose-response relationships for radiation-induced thyroid cancer and thyroid nodules: evidence for the prolonged effects of radiation on the thyroid
ARTHUR B Schneider, ELAINE Ron, Jay Lubin, Marilyn Stovall, and Theresa C Gierlowski · 1993
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Mixture density networks
Christopher M Bishop · 1994
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Jianqing Fan, Wenyang Zhang, et al · 1999
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Sun exposure and pterygium of the eye: a dose-response curve
Timothy J Threlfall and Dallas R English · 1999
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The role of the propensity score in estimating dose-response functions
Guido W Imbens · 2000
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Smoothing spline estimation for varying coefficient models with repeatedly measured dependent variables
Chin-Tsang Chiang, John A Rice, and Colin O Wu · 2001
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Approximation with artificial neural networks
Balázs Csanád Csáji et al · 2001
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Rademacher and gaussian complexities: Risk bounds and structural results
Peter L Bartlett and Shahar Mendelson · 2002
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Local asymptotics for polynomial spline regression
Jianhua Z Huang et al · 2003
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The propensity score with continuous treatments
Keisuke Hirano and Guido W Imbens · 2004
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Polynomial spline estimation and inference for varying coefficient models with longitudinal data
Jianhua Z Huang, Colin O Wu, and Lan Zhou · 2004
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Causal inference with general treatment regimes: Generalizing the propensity score
Kosuke Imai and David A Van Dyk · 2004
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Targeted maximum likelihood learning
Mark J Van Der Laan and Daniel Rubin · 2006
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Bag of words data set, 2008
David Newman · 2008
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A hypercube-based encoding for evolving large-scale neural networks
Kenneth O Stanley, David B D’Ambrosio, and Jason Gauci · 2009
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Bart: Bayesian additive regression trees
Hugh A Chipman, Edward I George, Robert E McCulloch, et al · 2010
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Bayesian nonparametric modeling for causal inference
Jennifer L Hill · 2011
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Stacked convolutional auto-encoders for hierarchical feature extraction
Jonathan Masci, Ueli Meier, Dan Cireşan, and Jürgen Schmidhuber · 2011
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Targeted learning: causal inference for observational and experimental data
Mark J Van der Laan and Sherri Rose · 2011
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Package ‘causaldrf’
Douglas Galagate, Joseph Schafer, and Maintainer Douglas Galagate · 2015
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A functional varying-coefficient single-index model for functional response data
Jialiang Li, Chao Huang, Zhub Hongtu, and Alzheimer’s Disease Neuroimaging Initiative · 2017
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Causal effect inference with deep latent-variable models
Christos Louizos, Uri Shalit, Joris M Mooij, David Sontag, Richard Zemel, and Max Welling · 2017
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Estimating individual treatment effect: generalization bounds and algorithms
Uri Shalit, Fredrik D Johansson, and David Sontag · 2017
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Double/debiased machine learning for treatment and structural parameters, 2018
Victor Chernozhukov, Denis Chetverikov, Mert Demirer, Esther Duflo, Christian Hansen, Whitney Newey, and James Robins · 2018
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Max H Farrell, Tengyuan Liang, and Sanjog Misra · 2018
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Danilo Jimenez Rezende and Shakir Mohamed · 2015
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Varying-coefficient additive models for functional data
Xiaoke Zhang and Jane-Ling Wang · 2015
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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
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David Ha, Andrew Dai, and Quoc V Le · 2016
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Learning representations for counterfactual inference
Fredrik Johansson, Uri Shalit, and David Sontag · 2016
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Package ‘bartmachine’
Adam Kapelner, Justin Bleich, Maintainer Adam Kapelner, and SystemRequirements Java · 2016
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Covariate balancing propensity score for a continuous treatment: Application to the efficacy of political advertisements
Christian Fong, Chad Hazlett, Kosuke Imai, et al · 2018
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Package ‘grf’, 2018
Julie Tibshirani, Susan Athey, Stefan Wager, Rina Friedberg, Luke Miner, Marvin Wright, Maintainer Julie Tibshirani, LinkingTo Rcpp, RcppEigen Imports DiceKriging, and GNU SystemRequirements · 2018
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Conditional density estimation with bayesian normalising flows
Brian L Trippe and Richard E Turner · 2018
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Estimation and inference of heterogeneous treatment effects using random forests
Stefan Wager and Susan Athey · 2018
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Ganite: Estimation of individualized treatment effects using generative adversarial nets
Jinsung Yoon, James Jordon, and Mihaela van der Schaar · 2018
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Conditional density estimation with neural networks: Best practices and benchmarks
Jonas Rothfuss, Fabio Ferreira, Simon Walther, and Maxim Ulrich · 2019
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Learning counterfactual representations for estimating individual dose-response curves
Patrick Schwab, Lorenz Linhardt, Stefan Bauer, Joachim M Buhmann, and Walter Karlen · 2019
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Adapting neural networks for the estimation of treatment effects
Claudia Shi, David Blei, and Victor Veitch · 2019
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Finite mixture of varying coefficient model: Estimation and component selection
Mao Ye, Zhao-Hua Lu, Yimei Li, and Xinyuan Song · 2019
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Estimating the effects of continuous-valued interventions using generative adversarial networks
Ioana Bica, James Jordon, and Mihaela van der Schaar · 2020
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