We develop regression diagnostics for functional regression models which relate a functional response to predictor variables that can be multivariate vectors or random functions. ...
Background: Carbohydrates are involved in a variety of fundamental biological processes and pathological situations. They therefore have a large pharmaceutical and diagnostic pote...
Abstract— We propose to improve the locomotive performance of humanoid robots by using approximated biped stepping and walking dynamics with reinforcement learning (RL). Although...
Jun Morimoto, Christopher G. Atkeson, Gen Endo, Go...
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
Recognition of a protein’s fold provides valuable information about its function. While many sequence-based homology prediction methods exist, an important challenge remains: tw...