30 citations · 80 across the 8 of their papers we have counts for
8 papers
TimeTok: Granularity-Controllable Time-Series Generation via Hierarchical Tokenization
Seokhyun Lee, Jaeho Kim, Changjun Oh +2
Time-series data are inherently multiscale, spanning diverse temporal granularities from coarse trends to fine-scale dynamics. However, existing time-series generative models provi…
Stochastic Encodings for Active Feature Acquisition
Alexander Norcliffe, Changhee Lee, Fergus Imrie +2
Active Feature Acquisition is an instance-wise, sequential decision making problem. The aim is to dynamically select which feature to measure based on current observations, indepen…
Domain-adapted large language models for classifying nuclear medicine reports
Zachary Huemann, Changhee Lee, Junjie Hu +2
With the growing use of transformer-based language models in medicine, it is unclear how well these models generalize to nuclear medicine which has domain-specific vocabulary and u…
T-Phenotype: Discovering Phenotypes of Predictive Temporal Patterns in Disease Progression
Yuchao Qin, Mihaela van der Schaar, Changhee Lee
Clustering time-series data in healthcare is crucial for clinical phenotyping to understand patients' disease progression patterns and to design treatment guidelines tailored to ho…
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data
Alicia Curth, Changhee Lee, Mihaela van der Schaar
We study the problem of inferring heterogeneous treatment effects from time-to-event data. While both the related problems of (i) estimating treatment effects for binary or continu…
A Variational Information Bottleneck Approach to Multi-Omics Data Integration
Changhee Lee, Mihaela van der Schaar
Integration of data from multiple omics techniques is becoming increasingly important in biomedical research. Due to non-uniformity and technical limitations in omics platforms, su…