Causal Discovery Toolbox: Uncover causal relationships in Python

The central role of the propensity score in observational studies for causal effects

Paul R Rosenbaum and Donald B Rubin · 1983

Earlier work this paper cites.

Causation, prediction, and search

Peter Spirtes, Clark N Glymour, and Richard Scheines · 2000

Earlier work this paper cites.

Optimal structure identification with greedy search

David Maxwell Chickering · 2002

Earlier work this paper cites.

Algorithms for large scale markov blanket discovery

Ioannis Tsamardinos, Constantin F Aliferis, and Alexander R Statnikov · 2003

Earlier work this paper cites.

Sparse inverse covariance estimation with the graphical lasso

Jerome Friedman, Trevor Hastie, and Robert Tibshirani · 2008

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.

Information theoretic measures for clusterings comparison: Variants, properties, normalization and correction for chance

Nguyen Xuan Vinh, Julien Epps, and James Bailey · 2010

Cited alongside, same era.

Network deconvolution as a general method to distinguish direct dependencies in networks

Soheil Feizi, Daniel Marbach, Muriel Médard, and Manolis Kellis · 2013

Cited alongside, same era.

Chalearn cause effect pairs challenge, 2013

Isabelle Guyon · 2013

Cited alongside, same era.

Cam: Causal additive models, high-dimensional order search and penalized regression

Peter Bühlmann, Jonas Peters, Jan Ernest, et al · 2014

Cited alongside, same era.

Towards a learning theory of cause-effect inference

David Lopez-Paz, Krikamol Muandet, Bernhard Schölkopf, and Ilya O Tolstikhin · 2015

Cited alongside, same era.

Conditional distribution variability measures for causality detection

Learning functional causal models with generative neural networks

Olivier Goudet, Diviyan Kalainathan, et al · 2017

Later among the works it cites.

Automatic differentiation in pytorch

Adam Paszke, Sam Gross, Soumith Chintala, et al · 2017

Later among the works it cites.

Approximate kernel-based conditional independence tests for fast non-parametric causal discovery

Eric V Strobl, Kun Zhang, and Shyam Visweswaran · 2017

Later among the works it cites.

Sam: Structural agnostic model, causal discovery and penalized adversarial learning

Diviyan Kalainathan, Olivier Goudet, et al · 2018

Later among the works it cites.

Package ‘pcalg’

Markus Kalisch, Alain Hauser, et al · 2018

Later among the works it cites.

Package ‘bnlearn’, 2018

Marco Scutari · 2018

Later among the works it cites.