The Multi-Output Gaussian Process Toolkit is a Python toolkit for training and interpreting Gaussian ... The toolkit is mainly targeted to time-series, and includes plotting functions for the case of ...

We report an educational tool for the upper level undergraduate quantum chemistry or quantum physics course that uses a symbolic approach via the PySyComp Python library ... Students can also plot ...

The most common techniques include linear regression, linear ridge regression, k-nearest neighbors regression, kernel ridge regression, Gaussian process regression, decision tree regression and neural ...

Using 2D tissue slices to decipher features of a 3D tissue is computationally challenging and leaves a lot of questions unanswered. A new method called Gaussian Process Spatial Alignment (GPSA) can ...

pyDARN is an open-source Python-based library developed specifically ... projections.py module for use with all geospatial plotting as a keyword rather than an addition to the axis. The installation ...

While researchers have traditionally employed Gaussian processes (GP) for specifying prior and posterior distributions over functions, this approach becomes computationally expensive when scaled, is ...

A 2D Gaussian distribution shown in a 3D plot. Note the higher values towards ... made up of the pixel values calculated through the process. For grayscale images, it’s that simple.