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Counterfactual estimation using synthetic controls is one of the most successful recent methodological developments in causal inference.
Predictability: A problem partly solved
Edward N Lorenz · 1996
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Marginal structural models and causal inference in epidemiology, 2000
James M Robins, Miguel Angel Hernan, and Babette Brumback · 2000
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The economic costs of conflict: A case study of the basque country
Alberto Abadie and Javier Gardeazabal · 2003
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Differential equations driven by rough paths
Terry J Lyons, Michael Caruana, and Thierry Lévy · 2007
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Constructing inverse probability weights for marginal structural models
Stephen R Cole and Miguel A Hernán · 2008
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Covariate shift by kernel mean matching
Arthur Gretton, Alex Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, and Bernhard Schölkopf · 2009
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Synthetic control methods for comparative case studies: Estimating the effect of california’s tobacco control program
Alberto Abadie, Alexis Diamond, and Jens Hainmueller · 2010
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Did the 2007 legal arizona workers act reduce the state’s unauthorized immigrant population?
Sarah Bohn, Magnus Lofstrom, and Steven Raphael · 2014
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Bayesian dynamical systems modelling in the social sciences
Shyam Ranganathan, Viktoria Spaiser, Richard P Mann, and David JT Sumpter · 2014
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Continuous control with deep reinforcement learning
Timothy P Lillicrap, Jonathan J Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra · 2015
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Balancing, regression, difference-in-differences and synthetic control methods: A synthesis
Nikolay Doudchenko and Guido W Imbens · 2016
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Estimating the effect of the emu on current account balances: A synthetic control approach
David Hope · 2016
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Effect of democratic reforms on child mortality: a synthetic control analysis
Hannah Pieters, Daniele Curzi, Alessandro Olper, and Johan Swinnen · 2016
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Credible research designs for minimum wage studies: A response to neumark, salas, and wascher
Sylvia Allegretto, Arindrajit Dube, Michael Reich, and Ben Zipperer · 2017
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The wage impact of the marielitos: A reappraisal
George J Borjas · 2017
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An exact and robust conformal inference method for counterfactual and synthetic controls
Victor Chernozhukov, Kaspar Wuthrich, and Yinchu Zhu · 2017
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Understanding the political economy of the eurozone crisis
Jeffry Frieden and Stefanie Walter · 2017
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A framework for synthetic control methods with high-dimensional, micro-level data: evaluating a neighborhood-specific crime intervention
Michael W Robbins, Jessica Saunders, and Beau Kilmer · 2017
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Gru-ode-bayes: Continuous modeling of sporadically-observed time series
Edward De Brouwer, Jaak Simm, Adam Arany, and Yves Moreau · 2019
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Augmented neural odes
Emilien Dupont, Arnaud Doucet, and Yee Whye Teh · 2019
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On chaotic dynamics in transcription factors and the associated effects in differential gene regulation
Mathias L Heltberg, Sandeep Krishna, and Mogens H Jensen · 2019
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Neural sde: Stabilizing neural ode networks with stochastic noise
Xuanqing Liu, Si Si, Qin Cao, Sanjiv Kumar, and Cho-Jui Hsieh · 2019
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Latent odes for irregularly-sampled time series
Yulia Rubanova, Ricky TQ Chen, and David Duvenaud · 2019
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Reliable decision support using counterfactual models
Peter Schulam and Suchi Saria · 2017
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Hossein Soleimani, Adarsh Subbaswamy, and Suchi Saria · 2017
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Robust synthetic control
Muhammad Amjad, Devavrat Shah, and Dennis Shen · 2018
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Matrix completion methods for causal panel data models
Susan Athey, Mohsen Bayati, Nikolay Doudchenko, Guido Imbens, and Khashayar Khosravi · 2018
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Synthetic control methodology as a tool for evaluating population-level health interventions
Janet Bouttell, Peter Craig, James Lewsey, Mark Robinson, and Frank Popham · 2018
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Neural ordinary differential equations
Ricky TQ Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018
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Using synthetic controls: Feasibility, data requirements, and methodological aspects
Alberto Abadie · 2019
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Belinda Tzen and Maxim Raginsky · 2019
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Ioana Bica, Ahmed M Alaa, James Jordon, and Mihaela van der Schaar · 2020
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Learning neural event functions for ordinary differential equations
Ricky TQ Chen, Brandon Amos, and Maximilian Nickel · 2020
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Dynamical systems theory for causal inference with application to synthetic control methods
Yi Ding and Panos Toulis · 2020
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Neural controlled differential equations for irregular time series
Patrick Kidger, James Morrill, James Foster, and Terry Lyons · 2020
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Sde-net: Equipping deep neural networks with uncertainty estimates
Lingkai Kong, Jimeng Sun, and Chao Zhang · 2020
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Scalable gradients and variational inference for stochastic differential equations
Xuechen Li, Ting-Kam Leonard Wong, Ricky TQ Chen, and David K Duvenaud · 2020
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Approximation capabilities of neural odes and invertible residual networks
Han Zhang, Xi Gao, Jacob Unterman, and Tom Arodz · 2020
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