Structural Intervention Distance (SID) for Evaluating Causal Graphs

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Structural Intervention Distance (SID) for Evaluating Causal Graphs

5 June 2013

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Papers citing "Structural Intervention Distance (SID) for Evaluating Causal Graphs"

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Title
CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models Benjamin Herdeanu Juan Nathaniel Carla Roesch Jatan Buch Gregor Ramien Johannes Haux Pierre Gentine CML AI4CE 102 0 0 22 May 2025
Towards Federated Bayesian Network Structure Learning with Continuous Optimization Ignavier Ng Kun Zhang FedML 91 38 0 18 Oct 2021
A survey of Bayesian Network structure learning N. K. Kitson Anthony C. Constantinou Zhi-gao Guo Yang Liu Kiattikun Chobtham CML 106 198 0 23 Sep 2021
Efficient Neural Causal Discovery without Acyclicity Constraints Phillip Lippe Taco S. Cohen E. Gavves CML 96 72 0 22 Jul 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 147 305 0 03 Mar 2021
On the Convergence of Continuous Constrained Optimization for Structure Learning Ignavier Ng Sébastien Lachapelle Nan Rosemary Ke Simon Lacoste-Julien Kun Zhang 105 38 0 23 Nov 2020
Differentiable Causal Discovery from Interventional Data P. Brouillard Sébastien Lachapelle Alexandre Lacoste Simon Lacoste-Julien Alexandre Drouin CML 87 191 0 03 Jul 2020
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs Ignavier Ng AmirEmad Ghassami Kun Zhang CML 87 189 0 17 Jun 2020
Approximate Causal Abstraction Sander Beckers F. Eberhardt Joseph Y. Halpern 98 53 0 27 Jun 2019
Gradient-Based Neural DAG Learning Sébastien Lachapelle P. Brouillard T. Deleu Simon Lacoste-Julien BDL CML 105 276 0 05 Jun 2019
Evaluating structure learning algorithms with a balanced scoring function Anthony C. Constantinou CML 89 18 0 29 May 2019
Learning Functional Causal Models with Generative Neural Networks Hugo Jair Escalante Sergio Escalera Xavier Baro Isabelle M Guyon Umut Güçlü Marcel van Gerven CML BDL 105 108 0 15 Sep 2017
Comparative Benchmarking of Causal Discovery Techniques Karamjit Singh Garima Gupta Vartika Tewari Gautam M. Shroff CML 107 13 0 18 Aug 2017
Kernel-based Tests for Joint Independence Niklas Pfister Peter Buhlmann Bernhard Schölkopf J. Peters 93 186 0 01 Mar 2016
A Complete Generalized Adjustment Criterion Emilija Perković J. Textor M. Kalisch Marloes H. Maathuis OffRL CML 72 73 0 06 Jul 2015
Partition MCMC for inference on acyclic digraphs Jack Kuipers G. Moffa 125 92 0 20 Apr 2015
Exact Estimation of Multiple Directed Acyclic Graphs Chris J. Oates Jim Q. Smith S. Mukherjee James Cussens 81 40 0 04 Apr 2014
CAM: Causal additive models, high-dimensional order search and penalized regression Peter Buhlmann J. Peters J. Ernest CML 160 326 0 06 Oct 2013
Causal Discovery with Continuous Additive Noise Models Jonas Peters Joris Mooij Dominik Janzing Bernhard Schölkopf CML 157 577 0 26 Sep 2013