Alexander Marx

Alexander Marx

Postdoc Fellow

alexander.marx(at)inf.ethz.ch

ETH AI Center

ETH Zürich

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Approximating Algorithmic Conditional Independence for Discrete Data

Conference paper

Alexander Marx, Jilles Vreeken
First AAAI Spring Symposium Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-based AI, Stanford, 2019
R-Project
Cite

Cite

APA
Marx, A., & Vreeken, J. (2019). Approximating Algorithmic Conditional Independence for Discrete Data. In First AAAI Spring Symposium Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-based AI, Stanford.

Chicago/Turabian
Marx, Alexander, and Jilles Vreeken. “Approximating Algorithmic Conditional Independence for Discrete Data.” In First AAAI Spring Symposium Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-Based AI, Stanford, 2019.

MLA
Marx, Alexander, and Jilles Vreeken. “Approximating Algorithmic Conditional Independence for Discrete Data.” First AAAI Spring Symposium Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-Based AI, Stanford, 2019.

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