Gaussian Process Regression for Materials and Molecules
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The rapid development of the Internet has created new opportunities for teaching in general and it is our aim to show how the current evolution can best be exploited for crystallography education in particular. Currently, we can find a very large selection ...
In order to achieve reliable information about deterioration, it is important to differentiate between changes in structural behaviour due to service loading (temperature, wind and traffic) and changes resulting from damage when interpreting measurement da ...
In this paper we present a solution for eye gaze detection from a wireless head mounted camera designed for children aged between 6 months and 18 months. Due to the constraints of working with very young children, the system does not seek to be as accurate ...
This letter provides a unified mean-square performance analysis of the class of data reusing adaptive algorithms. The derivation relies on energy conservation arguments, and it does not restrict the regression data to being Gaussian. Simulation results sho ...
FMRI time course processing is traditionally performed using linear regression followed by statistical hypothesis testing. While this analysis method is robust against noise, it relies strongly on the signal model. In this paper, we propose a non-parametri ...
Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2007
FMRI time course processing is traditionally performed using linear regression followed by statistical hypothesis testing. While this analysis method is robust against noise, it relies strongly on the signal model. In this paper, we propose a non-parametri ...
The paper develops a unified approach to the transient analysis of adaptive filters with error nonlinearities. In addition to deriving earlier results in a unified manner, the approach also leads to new performance results without restricting the regressio ...
The computation required for Gaussian process regression with n training examples is about O(n^3) during training and O(n) for each prediction. This makes Gaussian process regression too slow for large datasets. In this paper, we present a fast approximati ...
Most analytical results on affine projection algorithms assume special regression models or Gaussian regression data. The available analyses also treat different affine projection filters separately. This paper provides a unified treatment of the transient ...