On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables

4 July 2012

Papers citing "On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables"

18 / 18 papers shown

Title
Event-Triggered Nonlinear Model Predictive Control for Cooperative Cable-Suspended Payload Transportation with Multi-Quadrotors Tohid Kargar Tasooji Sakineh Khodadadi Guangjun Liu 30 0 0 26 Mar 2025
Passive learning of active causal strategies in agents and language models Andrew Kyle Lampinen Stephanie C. Y. Chan Ishita Dasgupta A. Nam Jane X. Wang 29 15 0 25 May 2023
A Survey on Causal Discovery: Theory and Practice Alessio Zanga Fabio Stella CML 27 38 0 17 May 2023
DiscoGen: Learning to Discover Gene Regulatory Networks Nan Rosemary Ke Sara-Jane Dunn J. Bornschein Silvia Chiappa Mélanie Rey ... David Barrett M. Botvinick Anirudh Goyal Michael C. Mozer Danilo Jimenez Rezende BDL CML 19 4 0 12 Apr 2023
Linear Causal Disentanglement via Interventions C. Squires A. Seigal Salil Bhate Caroline Uhler CML 23 66 0 29 Nov 2022
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis Ronan Perry Julius von Kügelgen Bernhard Schölkopf 38 48 0 04 Jun 2022
BaCaDI: Bayesian Causal Discovery with Unknown Interventions Alexander Hagele Jonas Rothfuss Lars Lorch Vignesh Ram Somnath Bernhard Schölkopf Andreas Krause CML BDL 41 19 0 03 Jun 2022
Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications Marcel Wienöbst Max Bannach Maciej Liskiewicz 27 10 0 05 May 2022
Universal Lower Bound for Learning Causal DAGs with Atomic Interventions Vibhor Porwal P. Srivastava Gaurav Sinha CML 31 2 0 09 Nov 2021
Learning Neural Causal Models with Active Interventions Nino Scherrer O. Bilaniuk Yashas Annadani Anirudh Goyal Patrick Schwab Bernhard Schölkopf Michael C. Mozer Yoshua Bengio Stefan Bauer Nan Rosemary Ke CML 33 42 0 06 Sep 2021
LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments Ali AhmadiTeshnizi Saber Salehkaleybar Negar Kiyavash CML 21 10 0 17 Jun 2020
Learning Neural Causal Models from Unknown Interventions Nan Rosemary Ke O. Bilaniuk Anirudh Goyal Stefan Bauer Hugo Larochelle Bernhard Schölkopf Michael C. Mozer C. Pal Yoshua Bengio CML OOD 27 168 0 02 Oct 2019
Size of Interventional Markov Equivalence Classes in Random DAG Models Dmitriy A. Katz Karthikeyan Shanmugam C. Squires Caroline Uhler CML 27 9 0 05 Mar 2019
Causal Queries from Observational Data in Biological Systems via Bayesian Networks: An Empirical Study in Small Networks Alex E. White Matthieu Vignes CML 15 5 0 04 May 2018
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees AmirEmad Ghassami Saber Salehkaleybar Negar Kiyavash Kun Zhang CML 42 22 0 05 Feb 2018
Causal Network Learning from Multiple Interventions of Unknown Manipulated Targets Y. He Z. Geng CML 45 13 0 27 Oct 2016
Causal Inference in the Presence of Latent Variables and Selection Bias Peter Spirtes Christopher Meek Thomas S. Richardson CML 147 435 0 20 Feb 2013
Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs Alain Hauser Peter Buhlmann CML 43 420 0 14 Apr 2011