Minimax Structured Neural Tangent Kernel in Estimating Average Treatment Effect Confounded by Image Covariate

Comparing Manifold-Constrained Gaussian Processes and Physics-Inspired Neural Networks for Parameter Inference in Epidemiological Models

Pixels, Priors, and Precision: Bayesian Approaches to Image Reconstruction

Improving Sampling and Function Approximation in Machine Learning Methods for Solving Partial Differential Equations

Applications of Closed-loop Control in Biomedical Interventions: From Neural Modulation to Diabetes Management

Automatic Hyperparameter Tuning in Physics-Based Distortion Correction for Diffusion Tensor Imaging

Modified Functional Principal Component Regression

Estimating Population Parameters of Fatal Police Shootings in America

Reinforcement Learning with Manifold Optimization