no code implementations • 27 Mar 2024 • Alan D. Kaplan, Priyadip Ray, John D. Greene, Vincent X. Liu
Inference algorithms are derived that use partial data to infer properties of the complete sequences, including their length and presence of specific values.
no code implementations • 15 Apr 2022 • Alan D. Kaplan, John D. Greene, Vincent X. Liu, Priyadip Ray
We develop an unsupervised probabilistic model for heterogeneous Electronic Health Record (EHR) data.
1 code implementation • 10 Apr 2020 • Sam Nguyen, Brenda Ng, Alan D. Kaplan, Priyadip Ray
We also investigate the transferability of BAnD's extracted features on unseen HCP tasks, either by freezing the spatial feature extraction layers and retraining the temporal model, or finetuning the entire model.
no code implementations • 13 Oct 2019 • Rui Meng, Herbert Lee, Soper Braden, Priyadip Ray
An issue faced by SGP, especially in latent variable models, is the inefficient learning of the inducing inputs, which leads to poor model prediction.
no code implementations • 13 Oct 2019 • Rui Meng, Braden Soper, Herbert Lee, Vincent X. Liu, John D. Greene, Priyadip Ray
We propose multivariate nonstationary Gaussian processes for jointly modeling multiple clinical variables, where the key parameters, length-scales, standard deviations and the correlations between the observed output, are all time dependent.
no code implementations • 9 Jan 2018 • Brenden K. Petersen, Michael B. Mayhew, Kalvin O. E. Ogbuefi, John D. Greene, Vincent X. Liu, Priyadip Ray
Characterizing a patient's progression through stages of sepsis is critical for enabling risk stratification and adaptive, personalized treatment.
no code implementations • 14 Oct 2017 • Qunwei Li, Bhavya Kailkhura, Ryan Goldhahn, Priyadip Ray, Pramod K. Varshney
We also provide conditions on the erroneous updates for exact convergence to the optimal solution.