2 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
Bandwidth Selection in Kernel Density Estimation for Model Calibration
Han Zhou, Teodora Popordanoska, Matthew Blaschko
As deep learning models are increasingly deployed in high-stakes applications, providing well-calibrated uncertainty estimates has become as critical as achieving high predictive a…
Learning Longitudinal Health Representations from EHR and Wearable Data
Yuanyun Zhang, Han Zhou, Li Feng +2
Foundation models trained on electronic health records show strong performance on many clinical prediction tasks but are limited by sparse and irregular documentation. Wearable dev…
Bayesian Optimization over Bounded Domains with the Beta Product Kernel
Huy Hoang Nguyen, Han Zhou, Matthew B. Blaschko +1
Bayesian optimization with Gaussian processes (GP) is commonly used to optimize black-box functions. The Matérn and the Radial Basis Function (RBF) covariance functions are used fr…
CVTN: Cross Variable and Temporal Integration for Time Series Forecasting
Han Zhou, Yuntian Chen
In multivariate time series forecasting, the Transformer architecture encounters two significant challenges: effectively mining features from historical sequences and avoiding over…
A Corrected Expected Improvement Acquisition Function Under Noisy Observations
Han Zhou, Xingchen Ma, Matthew B Blaschko
Sequential maximization of expected improvement (EI) is one of the most widely used policies in Bayesian optimization because of its simplicity and ability to handle noisy observat…