Snake robots have advantages of terrain adaptability over wheeled mobile robots and
traditional articulated robot arms because of their limbless thin body structure and high …

Data science and informatics tools have been proliferating recently within the computational
materials science and catalysis fields. This proliferation has spurned the creation of various …

Many information gathering problems require determining the set of points, for which an
unknown function takes value above or below some given threshold level. As a concrete …

We propose a novel sampling framework for inference in probabilistic models: an active
learning approach that converges more quickly (in wall-clock time) than Markov chain Monte …

In many real world problems, we want to infer some property of an expensive black-box
function f, given a budget of T function evaluations. One example is budget constrained …

Visual active search (VAS) has been proposed as a modeling framework in which visual
cues are used to guide exploration, with the goal of identifying regions of interest in a large …

Transfer learning algorithms are used when one has sufficient training data for one
supervised learning task (the source/training domain) but only very limited training data for a …

Probabilistic numerical computation formalises the connection between machine learning
and applied mathematics. Numerical algorithms approximate intractable quantities from …

Many problems in engineering design and simulation require balancing competing
objectives under the presence of uncertainty. Sample-efficient multiobjective optimization …

Transfer learning algorithms are used when one has sufficient training data for one
supervised learning task (the source task) but only very limited training data for a second …