Causal Inference on Discrete Data Using Additive Noise Models
Inferring the causal structure of a set of random variables from a finite sample of the joint distribution is an important problem in science. The case of two random variables is particularly challenging since no (conditional) independences can be exploited. Recent methods that are based on additive...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 33(2011), 12 vom: 04. Dez., Seite 2436-50 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2011
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
| Online verfügbar |
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