no code implementations • 16 Nov 2023 • Anna Wong, Shu Ge, Nassim Oufattole, Adam Dejl, Megan Su, Ardavan Saeedi, Li-wei H. Lehman
In this work, we use knowledge distillation via constrained variational inference to distill the knowledge of a powerful "teacher" neural network model with high predictive power to train a "student" latent variable model to learn interpretable hidden state representations to achieve high predictive performance for sepsis outcome prediction.
1 code implementation • 1 May 2023 • Akhilan Boopathy, Kevin Liu, Jaedong Hwang, Shu Ge, Asaad Mohammedsaleh, Ila Fiete
The measure of a machine learning algorithm is the difficulty of the tasks it can perform, and sufficiently difficult tasks are critical drivers of strong machine learning models.