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Books and Theses
- 2021
[b1]Jeeheh Oh:
Deep Learning Models for Clinical Data: Addressing Task Specific Structure. University of Michigan, USA, 2021
Conference and Workshop Papers
- 2021
- [c4]Erkin Ötles, Jeeheh Oh, Benjamin Li, Michelle Bochinski, Hyeon Joo
, Justin Ortwine, Erica Shenoy, Laraine Washer, Vincent B. Young, Krishna Rao, Jenna Wiens:
Mind the Performance Gap: Examining Dataset Shift During Prospective Validation. MLHC 2021: 506-534 - 2019
- [c3]Jeeheh Oh, Jiaxuan Wang, Shengpu Tang, Michael W. Sjoding, Jenna Wiens:
Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series. MLHC 2019: 27-52 - 2018
- [c2]Jiaxuan Wang, Jeeheh Oh, Haozhu Wang, Jenna Wiens:
Learning Credible Models. KDD 2018: 2417-2426 - [c1]Jeeheh Oh, Jiaxuan Wang, Jenna Wiens:
Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks. MLHC 2018: 332-347
Informal and Other Publications
- 2021
- [i4]Erkin Ötles, Jeeheh Oh, Benjamin Li, Michelle Bochinski, Hyeon Joo, Justin Ortwine, Erica Shenoy, Laraine Washer, Vincent B. Young, Krishna Rao, Jenna Wiens:
Mind the Performance Gap: Examining Dataset Shift During Prospective Validation. CoRR abs/2107.13964 (2021) - 2019
- [i3]Jeeheh Oh, Jiaxuan Wang, Shengpu Tang, Michael W. Sjoding, Jenna Wiens:
Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series. CoRR abs/1906.02898 (2019) - 2018
- [i2]Jeeheh Oh, Jiaxuan Wang, Jenna Wiens:
Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks. CoRR abs/1808.06725 (2018) - 2017
- [i1]Jiaxuan Wang, Jeeheh Oh, Jenna Wiens:
Learning Credible Models. CoRR abs/1711.03190 (2017)
Coauthor Index
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