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Causal Inference Under Interference And Network Uncertainty
Classical causal and statistical inference methods typically assume the observed data consists of independent realizations. However, in many applications this assumption is inappropriate due to a network of dependences between units in the data. Methods for estimating causal effects have been develo...
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| Veröffentlicht in: | Uncertain Artif Intell |
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| Hauptverfasser: | , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2019
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6935347/ https://ncbi.nlm.nih.gov/pubmed/31885520 |
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