| Augmenting existing deterioration indices with chest radiographs to predict clinical deterioration E Mu, S Jabbour, AV Dalca, J Guttag, J Wiens, MW Sjoding Plos one 17 (2), e0263922, 2022 | 7 | 2022 |
| Conditional Contrastive Networks E Mu, J Guttag NeurIPS 2022 First Table Representation Workshop, 2022 | 2 | 2022 |
| Generating Image-Specific Text Improves Fine-grained Image Classification E Mu, KM Lewis, AV Dalca, J Guttag arXiv preprint arXiv:2307.11315, 2023 | 1 | 2023 |
| Multi-similarity contrastive learning E Mu, J Guttag, M Makar arXiv preprint arXiv:2307.02712, 2023 | 1 | 2023 |
| Gist: Generating image-specific text for fine-grained object classification KM Lewis, E Mu, AV Dalca, J Guttag arXiv e-prints, arXiv: 2307.11315, 2023 | 1 | 2023 |
| 2387. Learning the Influence of Individual Clostridioides difficile Infections E Mu, M Makar, LR West, J Guttag, DC Rosenberg, ES Shenoy Open Forum Infectious Diseases 6 (Suppl 2), S824, 2019 | 1 | 2019 |
| Privacy preserving collaborative filtering E Mu, C Shao, V Miglani | 1 | 2017 |
| GIST: Generating Image-Specific Text for Fine-grained Object Representations KM Lewis, E Mu, AV Dalca, J Guttag | | 2023 |
| Multitask Contrastive Learning E Mu, J Guttag, M Makar | | 2023 |
| 350. Joint Modeling of EHR and CXR Data to Predict COVID-19 Deterioration E Mu, S Jabbour, M Sjoding, J Guttag, J Wiens, A Dalca Open Forum Infectious Diseases 8 (Suppl 1), S279, 2021 | | 2021 |
| Learning the magnitude and duration of influence of infections E Mu Massachusetts Institute of Technology, 2019 | | 2019 |
| Uncertainty Inclusive Contrastive Learning for Leveraging Synthetic Images F Cai, E Mu, J Guttag Synthetic Data for Computer Vision Workshop@ CVPR 2024, 0 | | |
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