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We posit that autoregressive flow models are well-suited to performing a range of causal inference tasks - ranging from causal discovery to making interventional and counterfactual predictions.
Ix. on the problem of the most efficient tests of statistical hypotheses
Jerzy Neyman and Egon Sharpe Pearson · 1933
Earlier work this paper cites.
Causation, Prediction and Search
Peter Spirtes, Clark Glymour, Richard Scheines, David Heckerman, Christopher Meek, and Thomas Richardson · 2000
Earlier work this paper cites.
Nonlinear causal discovery with additive noise models
Patrik O Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, and Bernhard Schölkopf · 2009
Earlier work this paper cites.
Causality
Judea Pearl · 2009
Earlier work this paper cites.
Causal inference in statistics: An overview
Judea Pearl et al · 2009
Earlier work this paper cites.
Pairwise Likelihood Ratios for Estimation of Non-Gaussian Structural Equation Models
Aapo Hyvärinen and Stephen M Smith · 2013
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Density estimation using real nvp
Laurent Dinh, Jascha Sohl-Dickstein, and Samy Bengio · 2016
Cited alongside, same era.
Distinguishing cause from effect using observational data: methods and benchmarks
Joris M Mooij, Jonas Peters, Dominik Janzing, Jakob Zscheischler, and Bernhard Schölkopf · 2016
Cited alongside, same era.
Cause-Effect Inference by Comparing Regression Errors
Patrick Blöbaum, Dominik Janzing, Takashi Washio, Shohei Shimizu, and Bernhard Schölkopf · 2018
Cited alongside, same era.
Neural autoregressive flows
Chin-Wei Huang, David Krueger, Alexandre Lacoste, and Aaron Courville · 2018
Cited alongside, same era.
A unified probabilistic model for learning latent factors and their connectivities from high-dimensional data
Ricardo Pio Monti and Aapo Hyvärinen · 2018
Later among the works it cites.
DAGs with NO TEARS: Continuous optimization for structure learning
Xun Zheng, Bryon Aragam, Pradeep K Ravikumar, and Eric P Xing · 2018
Later among the works it cites.
Causal discovery with general non-linear relationships using non-linear ICA
Ricardo Pio Monti, Kun Zhang, and Aapo Hyvärinen · 2019
Later among the works it cites.
Normalizing flows for probabilistic modeling and inference
George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, and Balaji Lakshminarayanan · 2019
Later among the works it cites.
Variational autoencoders and nonlinear ICA: A unifying framework
Ilyes Khemakhem, Diederik Kingma, Ricardo Monti, and Aapo Hyvarinen · 2020
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