Causality: Objectives and Assessment

Isabelle Guyon, Dominik Janzing, Bernhard Schölkopf; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:1-42

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Causal Inference

Judea Pearl; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:39-58

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Beware of the DAG!

A. Philip Dawid; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:59-86

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Causal Discovery as a Game

Frederick Eberhardt; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:87-96

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Sparse Causal Discovery in Multivariate Time Series

Stefan Haufe, Klaus-Robert Müller, Guido Nolte, Nicole Krämer; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:97-106

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Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions

Jan Lemeire, Kris Steenhaut; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:107-120

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Bayesian Algorithms for Causal Data Mining

Subramani Mani, Constantin F. Aliferis, Alexander Statnikov; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:121-136

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When causality matters for prediction: investigating the practical tradeoffs

Robert E. Tillman, Peter Spirtes; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:137-146

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Distinguishing between cause and effect

Joris Mooij, Dominik Janzing; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:147-156

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Distinguishing Causes from Effects using Nonlinear Acyclic Causal Models

Kun Zhang, Aapo Hyvärinen; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:157-164

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Structure Learning in Causal Cyclic Networks

Sleiman Itani, Mesrob Ohannessian, Karen Sachs, Garry P. Nolan, Munther A. Dahleh; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:165-176

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Causal learning without DAGs

David Duvenaud, Daniel Eaton, Kevin Murphy, Mark Schmidt; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:177-190

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Discover Local Causal Network around a Target to a Given Depth

You Zhou, Changzhang Wang, Jianxin Yin, Zhi Geng; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:191-202

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Fast Committee-Based Structure Learning

Ernest Mwebaze, John A. Quinn; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:203-214

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SIGNET: Boolean Rule Determination for Abscisic Acid Signaling

Jerry Jenkins; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:215-224

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The Use of Bernoulli Mixture Models for Identifying Corners of a Hypercube and Extracting Boolean Rules From Data

Mehreen Saeed; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:225-236

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Reverse Engineering of Asynchronous Boolean Networks via Minimum Explanatory Set and Maximum Likelihood

Cheng Zheng, Zhi Geng; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:237-248

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TIED: An Artificially Simulated Dataset with Multiple Markov Boundaries

Alexander Statnikov, Constantin F. Aliferis; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:249-256

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Learning Causal Models That Make Correct Manipulation Predictions With Time Series Data

Mark Voortman, Denver Dash, Marek J. Druzdzel; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:257-266

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Comparison of Granger Causality and Phase Slope Index

Guido Nolte, Andreas Ziehe, Nicole Krämer, Florin Popescu, Klaus-Robert Müller; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:267-276

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Causality Challenge: Benchmarking relevant signal components for effective monitoring and process control

Michael McCann, Yuhua Li, Liam Maguire, Adrian Johnston; Proceedings of Workshop on Causality: Objectives and Assessment at NIPS 2008, PMLR 6:277-288

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