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Structural Causal Models Are (Solvable by) Credal Networks
[article]
2020
arXiv
pre-print
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This contribution should be regarded as a systematic approach to represent structural causal models by credal networks and hence to systematically compute causal inferences. ...
This allows to exactly map a causal model into a credal network. ...
The tests have been performed by means of a Java library implementing all the techniques discussed in the paper. ...
arXiv:2008.00463v1
fatcat:kenlbdt5qjfwljgnjacwcr6iha
Robust Generalizations of Stochastic Derivative-Free Optimization
2021
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Two of them, the generalized lower confidence bound and a weighted maximum likelihood approach, outperform standard Bayesian optimization for specific types of problems. ...
Feasibility Study Implementations of "ApproxLP" and "CVE" are part of the publicly available java library CREDICI (CREDal Inference for Causal Inference) [Zaffalon et al., 2020] . ...
In a recent work, [Zaffalon et al., 2020] show that structural causal models can be solved by established algorithms for inference in credal nets [Augustin et al., 2014, Chapter 9 .5] such as "ApproxLP ...
doi:10.5282/ubm/epub.77441
fatcat:strgnvbi5fbgvkwq4nuw756tfe