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.

Approximations for Binary Gaussian Process Classification

We provide a comprehensive overview of many recent algorithms for approximate inference in Gaussian process models for probabilistic binary classification. The relationships between several approaches are elucidated theoretically, and the properties of the different algorithms are corroborated by experimental results. We examine both 1) the quality of the predictive distributions and 2) the suitability of the different marginal likelihood approximations for model selection (selecting hyperparameters) and compare to a gold standard based on MCMC. Interestingly, some methods produce good predictive distributions although their marginal likelihood approximations are poor. Strong conclusions are drawn about the methods: The Expectation Propagation algorithm is almost always the method of choice unless the computational budget is very tight. We also extend existing methods in various ways, and provide unifying code implementing all approaches.

Far-field intensity distribution and M-2 factor of hollow Gaussian beams

The far-field intensity distribution of hollow Gaussian beams was investigated based on scalar diffraction theory. An analytical expression of the M-2 factor of the beams was derived on the basis of the second-order moments. Moreover, numerical examples to illustrate our analytical results are given. (c) 2005 Optical Society of America.

Far-field intensity distribution of beam generated by Gaussian mirror resonator

Based on scalar diffraction theory, we investigated far-field intensity distribution (FFID) of beam generated by Gaussian mirror resonator. We found usable analytical expressions of diffracted field with respect to variation of diffraction parameters. Particular attention was paid to the parameters such as mirror spot size and radius of the Gaussian mirror, which determine the FFID. All analyses were limited to TEM00 fundamental mode. (c) 2004 Elsevier B.V. All rights reserved.

Propagation properties of a hard-edged diffracted beam generated by a Gaussian mirror resonator

Based on the scalar diffraction theory, the propagation and focusing properties of a hard-edged diffracted beam generated by a Gaussian mirror resonator were investigated. Explicit expressions for the field distribution of the truncated beam that propagates through a paraxial optical ABCD system were derived in detail. Numerical examples are given to illustrate our analytical results. (c) 2006 Optical Society of America.

Propagation properties of beam generated by Gaussian mirror resonator

Based on scalar diffraction theory, propagation properties of beam generated by Gaussian mirror resonator were investigated. Explicit expressions for the field distribution of the beam that propagate through a paraxial optical ABCD system were derived and numerical examples were given to illustrate our analytical results. (c) 2005 Elsevier B.V. All rights reserved.

Far-field intensity distribution, M-2 factor of beams generated by Gaussian mirror resonator

We investigated M-2 factor and far-field distribution of beams generated by Gaussian mirror resonator. And we found usable analytical expressions of the M2 factor and the far-field distribution intensity with respect to variation of diffraction parameters. Particular attention was paid to the parameters such as mirror spot size and reflectance of the Gaussian mirror. (c) 2006 Elsevier GrnbH. All rights reserved.

Propagation properties of beams generated by Gaussian mirror resonator in uniaxial crystals

Based on the paraxial vectorial theory of beams propagating in uniaxially anisotropic media, we have derived the analytical propagation equations of beams generated by Gaussian mirror resonator (GMR) in uniaxial crystals, and given the typical numerical example to illustrate our analytical results. Due to the anisotropy crystals, the ordinary and extraordinary beams originated by incident beams generated by GMR propagate with different diffraction lengths, thus the linear polarization state and axial symmetry of the incident beams generated by GMR do not remain during propagating in crystals. (c) 2006 Elsevier GmbH. All rights reserved.

Nonparaxial propagation of vectorial hollow Gaussian beams

Based on the vectorial Raleigh-Sommerfeld diffraction integral, the nonparaxial. propagation of vectorial hollow Gaussian beams (HGBs) in free space is studied. The far-field and paraxial cases can be treated as special cases of our general results. The typical numerical examples are given to illustrate our analytical results and comparisons between the different approximations present that the f parameter still plays an important role in determining the nonparaxiality of vectorial diffracted HGBs. (c) 2007 Optical Society of America.