When are Deep Networks really better than Random Forests at small sample sizes, and how? H Xu, KA Kinfu, W LeVine, S Panda, J Dey, M Ainsworth, YC Peng, ... arXiv preprint arXiv:2108.13637, 2021 | 28* | 2021 |
Representation Ensembling for Synergistic Lifelong Learning with Quasilinear Complexity J Dey, J Vogelstein, H Helm, W Levine, R Mehta, A Geisa, H Xu, ... | 16* | 2022 |
Deep Discriminative to Kernel Density Graph for In-and Out-of-distribution Calibrated Inference J Dey, W LeVine, H Xu, A De Silva, TM Tomita, A Geisa, T Chu, J Desman, ... arXiv preprint arXiv:2201.13001, 2022 | 2* | 2022 |
771: MACHINE LEARNING PREDICTION OF RESPONSIVENESS PHENOTYPES IN NON-NEUROLOGIC ICU PATIENTS H Xu, J Desman, Q Huang, M Igboko, A Kodibagkar, Z Wang, K Gong, ... Critical Care Medicine 50 (1), 379, 2022 | | 2022 |
Simplest Streaming Trees H Xu, J Dey, S Panda, JT Vogelstein arXiv preprint arXiv:2110.08483, 2021 | | 2021 |
A Computational Model to Predict Discharge Responsiveness in Non-Neurological ICU Patients H Xu, J Desman, MA Igboko, Q Huang, Z Wang, A Kodibagkar, K Gong, ... NCS 19th Annual Meeting, 2021 | | 2021 |
A Machine Learning Model to Predict Responsiveness in Non-Neurological ICU Patients H Xu, JM Desman, MA Igboko, Q Huang, Z Wang, A Kodibagkar, ... ESICM LIVES 2021, 2021 | | 2021 |
BioE Quarterly 2018 Winter Issue BEQ Staff | | 2018 |