the Gaussian ensembles are specific probability distributions over self-adjoint matrices whose entries are independently sampled from the gaussian distribution...

unitary conjugation. The Gaussian unitary ensemble models Hamiltonians lacking time-reversal symmetry. The Gaussian orthogonal ensemble GOE ( n ) {\displaystyle...

rectangular matrices are for those of Gaussian matrices. Web forms to evaluate bounds for the Gaussian ensemble are available at the Edinburgh Compressed...

past results in random matrix theory to show that, according to the Gaussian ensemble, a large number of matrices satisfy the restricted isometry property...

theory in connection with nonlinear operations on Gaussian noise. random matrix theory in Gaussian ensembles. Hermite polynomials were defined by Pierre-Simon...

distributions involved are Gaussian; when it is applicable, it is much more efficient than the particle filter. The ensemble Kalman filter (EnKF) is a...

instruction following. Product of experts Mixture models Mixture of gaussians Ensemble learning Baldacchino, Tara; Cross, Elizabeth J.; Worden, Keith; Rowson...

to be solvable by Painlevé transcendents. In general, consider a gaussian ensemble with beta value β {\displaystyle \beta } , with its diagonal entries...

classical chaotic system can be modeled by a random matrix from a Gaussian ensemble as the distance of a few spacings between eigenvalues of a chaotic...

circular ensembles are measures on spaces of unitary matrices introduced by Freeman Dyson as modifications of the Gaussian matrix ensembles. The three...

when the defining polynomial for X is sampled at random from the Gaussian ensemble induced by the Bombieri inner product. Two smooth cubic surfaces are...

Hermitian covariance matrix of n {\displaystyle n} zero-mean independent Gaussian random variables. It has support for p × p {\displaystyle p\times p} Hermitian...

algorithm for mixtures of Gaussian distributions via an iterative refinement approach employed by both k-means and Gaussian mixture modeling. They both...

assumed to be independent gaussian random processes with zero mean; the dynamic systems will be linear." Regardless of Gaussianity, however, if the process...

when "Ginibre ensemble" is spoken of, it by default means the β = 2 {\displaystyle \beta =2} case. By analogy with the gaussian ensembles, the cases of...

Non-homogeneous Gaussian regression (NGR) is a type of statistical regression analysis used in the atmospheric sciences as a way to convert ensemble forecasts...

members in the ensemble around the mean. However, in 2004, a generalisation of linear regression (now known as Nonhomogeneous Gaussian regression) was...

In probability theory and statistical mechanics, the Gaussian free field (GFF) is a Gaussian random field, a central model of random surfaces (random...

The isothermal–isobaric ensemble (constant temperature and constant pressure ensemble) is a statistical mechanical ensemble that maintains constant temperature...

emerge: At initialization (before training), the neural network ensemble is a zero-mean Gaussian process (GP). This means that distribution of functions is...

mipmap). Rather than sampling a single ray per pixel, the technique fits a gaussian to the conical frustum cast by the camera. This improvement effectively...

“credibility” to give to individual risk classifications. For jointly Gaussian ( X , Y ) {\displaystyle (X,Y)} , the fraction Var ⁡ ( E ⁡ [ Y ∣ X ] )...

kinetic information that an ensemble measurement cannot provide, especially when the system is under equilibrium with no ensemble/bulk signal change. Heterogeneity...

an integrated development environment Gaia-Sausage-Enceladus Gaussian Symplectic ensemble General somatic efferent fibers Georgian Soviet Encyclopedia...

eigenvalues of a random m × m Hermitian matrix drawn from the Gaussian unitary ensemble (GUE) form a determinantal point process on R {\displaystyle \mathbb...

independent identically distributed Gaussian noise, then the columns of T will also contain similarly identically distributed Gaussian noise (such a distribution...

\sigma (x)))} , where N {\displaystyle {\mathcal {N}}} stands for the gaussian distribution. They also argued for another reason for using ReLU: that...

neighbors were picked in proportion to their probability density under a Gaussian centered at x i {\displaystyle x_{i}} ." Now define p i j = p j ∣ i + p...

training a neural network to sequentially denoise images blurred with Gaussian noise. The model is trained to reverse the process of adding noise to an...

particular statistical ensemble (which, in turn, corresponds to a particular free energy). The most common statistical ensembles have named partition functions...