TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow Probability provides integration of ...

Abstract: This tutorial aims to provide an intuitive introduction to Gaussian process regression (GPR). GPR models have been widely used in machine learning applications due to their representation ...

Most patients with congenital heart disease survive into adulthood; however, residual abnormalities remain and management of the patients is life-long and personalized. Patients with surgical repair ...

Some machine learning models belong to either the “generative” or “discriminative” model categories. Yet what is the difference between these two categories of models? What does it mean for a model to ...

Manipulation of deformable objects has given rise to an important set of open problems in the field of robotics. Application areas include robotic surgery, household robotics, manufacturing, logistics ...

Accurate target detection and association are vital for the development of reliable target tracking, especially for cell tracking based on microscopy images due to the similarity of cells. We propose ...

This is not an officially supported Google product. Spatially referenced time series (i.e., spatiotemporal) datasets are ubiquitous in scientific, engineering, and business-intelligence applications.

How does one model a simple cell-signaling pathway? Consider a simple example consisting of a stimulant, an extracellular signal, an inhibitor of the signal, a G protein–coupled receptor, a G protein ...