Optimizing the Design of an Experiment using the ADOpy Package: An Introduction and Tutorial

서울대학교 중앙도서관

S-Space 소개

My S-Space

로그인이 필요합니다.

S-Space

Publications

Detailed Information

Optimizing the Design of an Experiment using the ADOpy Package: An Introduction and Tutorial

DC Field	Value	Language
dc.contributor.author	Myung, Jay I.	-
dc.contributor.author	Pitt, Mark A.	-
dc.contributor.author	Yang, Jaeyeong	-
dc.contributor.author	Ahn, Woo-Young	-
dc.date.accessioned	2024-05-16T01:46:06Z	-
dc.date.available	2024-05-16T01:46:06Z	-
dc.date.created	2024-04-17	-
dc.date.created	2024-04-17	-
dc.date.issued	2019	-
dc.identifier.citation	Proceedings of the 41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019, pp.19-20	-
dc.identifier.uri	https://hdl.handle.net/10371/202839	-
dc.language	영어	-
dc.publisher	The Cognitive Science Society	-
dc.title	Optimizing the Design of an Experiment using the ADOpy Package: An Introduction and Tutorial	-
dc.type	Article	-
dc.citation.journaltitle	Proceedings of the 41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019	-
dc.identifier.scopusid	2-s2.0-85139384348	-
dc.citation.endpage	20	-
dc.citation.startpage	19	-
dc.description.isOpenAccess	N	-
dc.contributor.affiliatedAuthor	Ahn, Woo-Young	-
dc.type.docType	Conference Paper	-
dc.description.journalClass	1	-
dc.subject.keywordAuthor	adaptive design optimization	-
dc.subject.keywordAuthor	autonomous experimentation	-
dc.subject.keywordAuthor	Bayesian active learning	-
dc.subject.keywordAuthor	computational cognition	-
dc.subject.keywordAuthor	Python software package	-