Academic Journal
Leveraging Autocorrelation in a Dilated CNN-LSTM Framework for Predicting the US Supreme Court Decisions
| Title: | Leveraging Autocorrelation in a Dilated CNN-LSTM Framework for Predicting the US Supreme Court Decisions |
|---|---|
| Authors: | Salman Abbasi, M., Munir, B., Jayaram, V., Rivas, P. |
| Source: | IEEE Access Access, IEEE. 13:161250-161261 2025 |
| Database: | IEEE Xplore Digital Library |
| FullText | Links: – Type: other Text: Availability: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.11162521 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/ACCESS.2025.3609282 PhysicalDescription: Pagination: PageCount: 12 StartPage: 161250 Titles: – TitleFull: Leveraging Autocorrelation in a Dilated CNN-LSTM Framework for Predicting the US Supreme Court Decisions Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Salman Abbasi, M. – PersonEntity: Name: NameFull: Munir, B. – PersonEntity: Name: NameFull: Jayaram, V. – PersonEntity: Name: NameFull: Rivas, P. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 21693536 – Type: issn-locals Value: edseee.IEEEJournals Numbering: – Type: volume Value: 13 Titles: – TitleFull: IEEE Access, Access, IEEE Type: main |
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