1.3k citations · 1.9k across the 11 of their papers we have counts for
11 papers
Machine Learning-guided Lipid Nanoparticle Design for mRNA Delivery
Daisy Yi Ding, Yuhui Zhang, Yuan Jia +1
While RNA technologies hold immense therapeutic potential in a range of applications from vaccination to gene editing, the broad implementation of these technologies is hindered by…
Semi-supervised Cooperative Learning for Multiomics Data Fusion
Daisy Yi Ding, Xiaotao Shen, Michael Snyder +1
Multiomics data fusion integrates diverse data modalities, ranging from transcriptomics to proteomics, to gain a comprehensive understanding of biological systems and enhance predi…
Cooperative learning for multiview analysis
Daisy Yi Ding, Shuangning Li, Balasubramanian Narasimhan +1
We propose a new method for supervised learning with multiple sets of features ("views"). The multiview problem is especially important in biology and medicine, where "-omics" data…
Handling Missing Data with Graph Representation Learning
Jiaxuan You, Xiaobai Ma, Daisy Yi Ding +2
Machine learning with missing data has been approached in two different ways, including feature imputation where missing feature values are estimated based on observed values, and…
Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare
Scott L. Fleming, Kuhan Jeyapragasan, Tony Duan +4
There is an emerging trend in the reinforcement learning for healthcare literature. In order to prepare longitudinal, irregularly sampled, clinical datasets for reinforcement learn…
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan, Anand Avati, Daisy Yi Ding +4
We present Natural Gradient Boosting (NGBoost), an algorithm for generic probabilistic prediction via gradient boosting. Typical regression models return a point estimate, conditio…