Simulating Counterfactuals
| dc.contributor.author | Karvanen, Juha | |
| dc.contributor.author | Tikka, Santtu | |
| dc.contributor.author | Vihola, Matti | |
| dc.date.accessioned | 2024-07-08T06:47:59Z | |
| dc.date.available | 2024-07-08T06:47:59Z | |
| dc.date.issued | 2024 | |
| dc.identifier.citation | Karvanen, J., Tikka, S., & Vihola, M. (2024). Simulating Counterfactuals. <i>Journal of Artificial Intelligence Research</i>, <i>80</i>, 835-857. <a href="https://doi.org/10.1613/jair.1.15579" target="_blank">https://doi.org/10.1613/jair.1.15579</a> | |
| dc.identifier.other | CONVID_220936808 | |
| dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/96324 | |
| dc.description.abstract | Counterfactual inference considers a hypothetical intervention in a parallel world that shares some evidence with the factual world. If the evidence specifies a conditional distribution on a manifold, counterfactuals may be analytically intractable. We present an algorithm for simulating values from a counterfactual distribution where conditions can be set on both discrete and continuous variables. We show that the proposed algorithm can be presented as a particle filter leading to asymptotically valid inference. The algorithm is applied to fairness analysis in credit-scoring. | en |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | eng | |
| dc.publisher | AI Access Foundation | |
| dc.relation.ispartofseries | Journal of Artificial Intelligence Research | |
| dc.rights | CC BY 4.0 | |
| dc.subject.other | bayesian networks | |
| dc.subject.other | causality | |
| dc.subject.other | machine learning | |
| dc.title | Simulating Counterfactuals | |
| dc.type | research article | |
| dc.identifier.urn | URN:NBN:fi:jyu-202407085151 | |
| dc.contributor.laitos | Matematiikan ja tilastotieteen laitos | fi |
| dc.contributor.laitos | Department of Mathematics and Statistics | en |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
| dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
| dc.description.reviewstatus | peerReviewed | |
| dc.format.pagerange | 835-857 | |
| dc.relation.issn | 1076-9757 | |
| dc.relation.volume | 80 | |
| dc.type.version | publishedVersion | |
| dc.rights.copyright | ©2024 The Authors. Published by AI Access Foundation | |
| dc.rights.accesslevel | openAccess | fi |
| dc.type.publication | article | |
| dc.relation.grantnumber | 346311 | |
| dc.relation.grantnumber | 331817 | |
| dc.subject.yso | algoritmit | |
| dc.subject.yso | kausaliteetti | |
| dc.subject.yso | koneoppiminen | |
| dc.format.content | fulltext | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p14524 | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p333 | |
| jyx.subject.uri | http://www.yso.fi/onto/yso/p21846 | |
| dc.rights.url | https://creativecommons.org/licenses/by/4.0/ | |
| dc.relation.doi | 10.1613/jair.1.15579 | |
| dc.relation.funder | Research Council of Finland | en |
| dc.relation.funder | Research Council of Finland | en |
| dc.relation.funder | Suomen Akatemia | fi |
| dc.relation.funder | Suomen Akatemia | fi |
| jyx.fundingprogram | Centre of Excellence, AoF | en |
| jyx.fundingprogram | Academy Project, AoF | en |
| jyx.fundingprogram | Huippuyksikkörahoitus, SA | fi |
| jyx.fundingprogram | Akatemiahanke, SA | fi |
| jyx.fundinginformation | CSC – IT Center for Science, Finland, is acknowledged for computational resources. MV was supported by Research Council of Finland (Finnish Centre of Excellence in Randomness and Structures, grant 346311). ST was supported by Research Council of Finland (PREDLIFE: Towards well-informed decisions: Predicting long-term effects of policy re-forms on life trajectories, grant 331817). | |
| dc.type.okm | A1 |
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