Noninvasive diagnosis of kidney diseases and assessment of the prognosis are still
challenges in clinical nephrology. Definition of biomarkers on the basis of proteome …

The field of clinical proteomics offers opportunities to identify new disease biomarkers in
body fluids, cells and tissues. These biomarkers can be used in clinical applications for …

We evaluate 179 classifiers arising from 17 families (discriminant analysis, Bayesian, neural
networks, support vector machines, decision trees, rule-based classifiers, boosting, bagging …

Gaussian process classification is a popular method with a number of appealing properties.
We show how to scale the model within a variational inducing point framework, out …

We develop stochastic variational inference, a scalable algorithm for approximating
posterior distributions. We develop this technique for a large class of probabilistic models …

Because of its availability, ease of collection, and correlation with physiology and pathology,
urine is an attractive source for clinical proteomics/peptidomics. However, the lack of …

Variational approximations facilitate approximate inference for the parameters in complex
statistical models and provide fast, deterministic alternatives to Monte Carlo methods …

Deep neural networks (DNNs) have excellent representative power and are state of the art
classifiers on many tasks. However, they often do not capture their own uncertainties well …

We provide a comprehensive overview of many recent algorithms for approximate inference
in Gaussian process models for probabilistic binary classification. The relationships between …

Deep neural networks (DNNs) extract thousands to millions of task-specific features during
model training for inference and decision-making. While visualizing these features is critical …