Bayesian policy distillation: Towards lightweight and fast neural policy networks.
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| Title: | Bayesian policy distillation: Towards lightweight and fast neural policy networks. |
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| Authors: | Kim, Jangwon1, Jang, Yoonsu1, Park, Jonghyeok2, Gil, Yoonhee1, Han, Soohee1,3, sooheehan@postech.ac.kr |
| Source: | Engineering Applications of Artificial Intelligence; Feb2026:Part B, Vol. 166, pN.PAG-N.PAG, 1p |
| Database: | Applied Science & Technology Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 191077146 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=191077146 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.engappai.2025.113539 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Titles: – TitleFull: Bayesian policy distillation: Towards lightweight and fast neural policy networks. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kim, Jangwon – PersonEntity: Name: NameFull: Jang, Yoonsu – PersonEntity: Name: NameFull: Park, Jonghyeok – PersonEntity: Name: NameFull: Gil, Yoonhee – PersonEntity: Name: NameFull: Han, Soohee IsPartOfRelationships: – BibEntity: Dates: – D: 16 M: 02 Text: Feb2026:Part B Type: published Y: 2026 Identifiers: – Type: issn-print Value: 09521976 Numbering: – Type: volume Value: 166 Titles: – TitleFull: Engineering Applications of Artificial Intelligence Type: main |
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