50 citations · 379 across the 27 of their papers we have counts for
27 papers
Analytical Charge Density Profile of Vortex Core in Weak-Coupling Superconductor
Chi-Ken Lu
Self-consistent Bogoliubov-de Gennes calculations have long shown that solving the Poisson equation inside a superconducting vortex turns a one-signed charge depletion into a modul…
A Log-Linear Analytics Approach to Cost Model Regularization for Inpatient Stays through Diagnostic Code Merging
Chi-Ken Lu, David Alonge, Nicole Richardson +1
Cost models in healthcare research must balance interpretability, accuracy, and parameter consistency. However, interpretable models often struggle to achieve both accuracy and con…
Bayesian inference with finitely wide neural networks
Chi-Ken Lu
The analytic inference, e.g. predictive distribution being in closed form, may be an appealing benefit for machine learning practitioners when they treat wide neural networks as Ga…
On Connecting Deep Trigonometric Networks with Deep Gaussian Processes: Covariance, Expressivity, and Neural Tangent Kernel
Chi-Ken Lu, Patrick Shafto
Deep Gaussian Process (DGP) as a model prior in Bayesian learning intuitively exploits the expressive power in function composition. DGPs also offer diverse modeling capabilities,…
Conditional Deep Gaussian Processes: empirical Bayes hyperdata learning
Chi-Ken Lu, Patrick Shafto
It is desirable to combine the expressive power of deep learning with Gaussian Process (GP) in one expressive Bayesian learning model. Deep kernel learning showed success in adopti…
Conditional Deep Gaussian Processes: multi-fidelity kernel learning
Chi-Ken Lu, Patrick Shafto
Deep Gaussian Processes (DGPs) were proposed as an expressive Bayesian model capable of a mathematically grounded estimation of uncertainty. The expressivity of DPGs results from n…