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Scaling recurrent models via orthogonal approximations in tensor trains. Mehta R, Chakraborty R, Xiong Y, Singh V. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019.
iFunMed: Integrative functional mediation analysis of GWAS and eQTL studies. Rojo C, Zhang Q, Keles S. Genetic Epidemiology 43(7):742-760.
Age-based versus risk-based mammography screening in women 40–49 years old: A cross-sectional study. Burnside ES, Trentham-Dietz A, Shafer CM, Hampton JM, Alagoz O, Cox JR, Mischo E, Schrager SB, Wilke LG. Radiology 292(2):321–328, 2019.
Sampling-free uncertainty estimation in gated recurrent units with applications to normative modeling in neuroimaging. Hwang SJ, Mehta R, Kim HJ, Johnson SC, Singh V. Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2019.
Augmenting subnetwork inference with information extracted from the scientific literature. Kiblawi S, Chasman D, Henning A, Park E, Poon H, Gould M, Ahlquist P, Craven M. PLoS Computational Biology 15(6): e1006758, 2019.
On training deep 3D CNN models with dependent samples in neuroimaging. Xiong Y, Kim HJ, Tangirala B, Mehta R, Johnson S, Singh V. Proceedings of the International Conference on Information Processing in Medical Imaging, 2019.
Machine learning for phenotyping opioid overdose events. Badger J, LaRose E, Mayer J, Bashiri F, Page D, Peissig P. Journal of Biomedical Informatics 94:103185, 2019.
Learning high-dimensional generalized linear autoregressive models. Hall E, Raskutti G, Willett R. IEEE Transactions on Information Theory 65(4):2401-22, 2019.
Understanding learned models by identifying important features at the right resolution. Lee K, Sood A, Craven M. Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), 2019.
Recursive Feature Elimination by Sensitivity Testing. Escanilla NS, Hellerstein L, Kleiman R, Kuang Z, Shull J, Page CD. Proceedings of the IEEE International Conference on Machine Learning and Applications, 2018.