Gaussian processes for machine learning (GPML) toolbox

The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library of simple mean and covariance functions and mechanisms to compose more complex ones. Several likelihood functions are supported including Gaussian and heavy-tailed for regression as well as others suitable for classification. Finally, a range of inference methods is provided, including exact and variational inference, Expectation Propagation, and Laplace’s method dealing with non-Gaussian likelihoods and FITC for dealing with large regression tasks.

Multivariable toolbox for use with MATLAB.

The authors describe a toolbox for the frequency-domain analysis and design of multivariable feedback systems, to be used with PC-Matlab, or Pro-Matlab. The principal model representations used by the toolbox are described. Its capabilities are illustrated by a worked design example, which shows the use of a Nyquist array method. Other design techniques supported by the toolbox are briefly reviewed.

CACSD, GUI's, and the multivariable frequency domain toolbox

This talk describes a new version of the Multivariable Frequency Domain Toolbox for Matlab. The intellectual issue which arises here is whether there is a role for Matlab-4 GUI facilities in a Toolbox which provides relatively low-level functionality, with a correspondingly random pattern of user interaction. My belief is that there is a role, but it is very restricted: in effect only for providing convenient 'viewing' facilities for low-level objects (which are multivariable frequency responses in the case of the MFD Toolbox). There is a more obvious role for a GUI with higher-level functions, such as frequency domain identification or parametric controller optimisation.

Manopt, a matlab toolbox for optimization on manifolds

Optimization on manifolds is a rapidly developing branch of nonlinear optimization. Its focus is on problems where the smooth geometry of the search space can be leveraged to design effcient numerical algorithms. In particular, optimization on manifolds is well-suited to deal with rank and orthogonality constraints. Such structured constraints appear pervasively in machine learning applications, including low-rank matrix completion, sensor network localization, camera network registration, independent component analysis, metric learning, dimensionality reduction and so on. The Manopt toolbox, available at www.manopt.org, is a user-friendly, documented piece of software dedicated to simplify experimenting with state of the art Riemannian optimization algorithms. By dealing internally with most of the differential geometry, the package aims particularly at lowering the entrance barrier. © 2014 Nicolas Boumal.

A computationally efficient software application for calculating vibration from underground railways

The PiP model is a software application with a user-friendly interface for calculating vibration from underground railways. This paper reports about the software with a focus on its latest version and the plans for future developments. The software calculates the Power Spectral Density of vibration due to a moving train on floating-slab track with track irregularity described by typical values of spectra for tracks with good, average and bad conditions. The latest version accounts for a tunnel embedded in a half space by employing a toolbox developed at K.U. Leuven which calculates Green's functions for a multi-layered half-space. © 2009 IOP Publishing Ltd.

Probing small molecule binding to amyloid fibrils.

Much effort has focussed in recent years on probing the interactions of small molecules with amyloid fibrils and other protein aggregates. Understanding and control of such interactions are important for the development of diagnostic and therapeutic strategies in situations where protein aggregation is associated with disease. In this perspective article we give an overview over the toolbox of biophysical methods for the study of such amyloid-small molecule interactions. We discuss in detail two recently developed techniques within this framework: linear dichroism, a promising extension of the more traditional spectroscopic techniques, and biosensing methods, where surface-bound amyloid fibrils are exposed to solutions of small molecules. Both techniques rely on the measurement of physical properties that are very directly linked to the binding of small molecules to amyloid aggregates and therefore provide an attractive route to probe these important interactions.