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D'ya like DAGs? A Survey on Structure Learning and Causal Discovery

3 March 2021

Papers citing "D'ya like DAGs? A Survey on Structure Learning and Causal Discovery"

43 / 143 papers shown

Title
Improving Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma Tim Salimans Rafal Jozefowicz Xi Chen Ilya Sutskever Max Welling BDL DRL 155 1,825 0 15 Jun 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 305 4,812 0 04 Jan 2016
High-dimensional consistency in score-based and hybrid structure learning Preetam Nandy Alain Hauser Marloes H. Maathuis 98 130 0 09 Jul 2015
Inferring large graphs using l1-penalized likelihood Magali Champion Victor Picheny Matthieu Vignes 74 21 0 08 Jul 2015
backShift: Learning causal cyclic graphs from unknown shift interventions Dominik Rothenhäusler C. Heinze J. Peters N. Meinshausen OOD 88 72 0 08 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 322 4,197 0 21 May 2015
MADE: Masked Autoencoder for Distribution Estimation M. Germain Karol Gregor Iain Murray Hugo Larochelle OOD SyDa UQCV 187 874 0 12 Feb 2015
A fast PC algorithm for high dimensional causal discovery with multi-core PCs T. Le Tao Hoang Jiuyong Li Lin Liu Huawen Liu 100 143 0 09 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
Distinguishing cause from effect using observational data: methods and benchmarks Joris M. Mooij J. Peters Dominik Janzing Jakob Zscheischler Bernhard Schölkopf CML 144 138 0 11 Dec 2014
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 253 8,429 0 28 Nov 2014
From Ordinary Differential Equations to Structural Causal Models: the deterministic case Joris Mooij Dominik Janzing Bernhard Schölkopf 124 105 0 09 Aug 2014
Bayesian Network Constraint-Based Structure Learning Algorithms: Parallel and Optimised Implementations in the bnlearn R Package M. Scutari CML 119 167 0 30 Jun 2014
Penalized Estimation of Directed Acyclic Graphs From Discrete Data J. Gu Fei Fu Qing Zhou CML 88 42 0 10 Mar 2014
Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets Sofia Triantafillou Ioannis Tsamardinos CML 149 151 0 10 Mar 2014
Concave Penalized Estimation of Sparse Gaussian Bayesian Networks Bryon Aragam Qing Zhou CML 116 107 0 04 Jan 2014
Black Box Variational Inference Rajesh Ranganath S. Gerrish David M. Blei DRL BDL 150 1,167 0 31 Dec 2013
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 458 16,922 0 20 Dec 2013
CAM: Causal additive models, high-dimensional order search and penalized regression Peter Buhlmann J. Peters J. Ernest CML 133 325 0 06 Oct 2013
Discovering Cyclic Causal Models with Latent Variables: A General SAT-Based Procedure Antti Hyttinen P. Hoyer F. Eberhardt Matti Järvisalo CML 95 90 0 26 Sep 2013
Structural Intervention Distance (SID) for Evaluating Causal Graphs J. Peters Peter Buhlmann CML 93 40 0 05 Jun 2013
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman D. Geiger D. M. Chickering TPM 119 3,984 0 27 Feb 2013
Learning Gaussian Networks D. Geiger David Heckerman TPM 84 500 0 27 Feb 2013
Causal Inference in the Presence of Latent Variables and Selection Bias Peter Spirtes Christopher Meek Thomas S. Richardson CML 206 448 0 20 Feb 2013
A Discovery Algorithm for Directed Cyclic Graphs Thomas S. Richardson CML 136 195 0 13 Feb 2013
Order-independent constraint-based causal structure learning Diego Colombo Marloes H. Maathuis CML 132 606 0 14 Nov 2012
Counterfactual Reasoning and Learning Systems Léon Bottou J. Peters J. Q. Candela Denis Xavier Charles D. M. Chickering Elon Portugaly Dipankar Ray Patrice Y. Simard Edward Snelson CML OffRL 396 787 0 11 Sep 2012
Nonparametric sparsity and regularization Lorenzo Rosasco S. Villa S. Mosci M. Santoro A. Verri 125 103 0 13 Aug 2012
Ordering-Based Search: A Simple and Effective Algorithm for Learning Bayesian Networks M. Teyssier D. Koller 166 375 0 04 Jul 2012
Adjacency-Faithfulness and Conservative Causal Inference Joseph Ramsey Jiji Zhang Peter Spirtes 114 276 0 27 Jun 2012
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 286 12,460 0 24 Jun 2012
$$\ell_0$-penalized maximum likelihood for sparse directed acyclic graphs$ $\ell_0$ -penalized maximum likelihood for sparse directed acyclic graphs Sara van de Geer Peter Buhlmann CML 158 83 0 24 May 2012
On the Identifiability of the Post-Nonlinear Causal Model Kun Zhang Aapo Hyvarinen CML 211 564 0 09 May 2012
Identifying confounders using additive noise models Dominik Janzing J. Peters Joris Mooij Bernhard Schölkopf CML 108 67 0 09 May 2012
On a Class of Bias-Amplifying Variables that Endanger Effect Estimates Judea Pearl CML 82 179 0 15 Mar 2012
Kernel-based Conditional Independence Test and Application in Causal Discovery Kun Zhang J. Peters Dominik Janzing Bernhard Schölkopf BDL CML 109 632 0 14 Feb 2012
Learning high-dimensional directed acyclic graphs with latent and selection variables Diego Colombo Marloes H. Maathuis M. Kalisch Thomas S. Richardson CML 132 467 0 29 Apr 2011
Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs Alain Hauser Peter Buhlmann CML 101 426 0 14 Apr 2011
A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning Stéphane Ross Geoffrey J. Gordon J. Andrew Bagnell OffRL 256 3,238 0 02 Nov 2010
Penalized Likelihood Methods for Estimation of Sparse High Dimensional Directed Acyclic Graphs Ali Shojaie George Michailidis CML 156 200 0 28 Nov 2009
Markov equivalence for ancestral graphs R. A. Ali Thomas S. Richardson Peter Spirtes 159 112 0 25 Aug 2009
A Kernel Method for the Two-Sample Problem Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alex Smola 241 2,365 0 15 May 2008
Causal inference using the algorithmic Markov condition Dominik Janzing Bernhard Schölkopf CML 163 307 0 23 Apr 2008