Detailed Information
Cited 0 time in 
Cited 0 time in 
Cited 0 time in
Metadata Downloads
Learning Invariant Representations of Molecules for Atomization Energy Prediction
Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Siamac Fazli | - |
| dc.date.accessioned | 2021-08-29T18:51:23Z | - |
| dc.date.available | 2021-08-29T18:51:23Z | - |
| dc.date.created | 2021-04-22 | - |
| dc.date.issued | 2012-12-04 | - |
| dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/45044 | - |
| dc.publisher | Queensland University | - |
| dc.title | Learning Invariant Representations of Molecules for Atomization Energy Prediction | - |
| dc.title.alternative | Learning Invariant Representations of Molecules for Atomization Energy Prediction | - |
| dc.type | Conference | - |
| dc.contributor.affiliatedAuthor | Siamac Fazli | - |
| dc.identifier.bibliographicCitation | Advances in Neural Information Processing Systems | - |
| dc.relation.isPartOf | Advances in Neural Information Processing Systems | - |
| dc.relation.isPartOf | Proceeding on Neural Information Processing Systems | - |
| dc.citation.title | Advances in Neural Information Processing Systems | - |
| dc.citation.conferencePlace | US | - |
| dc.citation.conferenceDate | 2012-12-03 | - |
| dc.type.rims | CONF | - |
| dc.description.journalClass | 1 | - |
- Files in This Item
- There are no files associated with this item.
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.