This release contains significant improvements to the GpRegressor class, including: A new option to select between the squared-exponential and rational-quadratic covariance functions, or provide a user-defined custom covariance function. A new option to use leave-one-out cross-validation to select hyper-parameter values instead of the marginal-likelihood. Significant improvements to numerical efficiency leading to reduce computation times
General New vignette Different Output between Stata and ggeffects. Changes to functions ggpr...
Fixed various bugs that appeared when testing after updating dependencies to numpy 1.15.0, scipy 1.3...
(rapidtide) Added new "--CVR" analysis type to generate calibrated CVR maps when given a CO2 regress...
Rather than assuming the mean of the Gaussian process is zero, GpRegressor now treats the mean as a ...
Added a new class GpLinearInverter for performing Gaussian-process linear inversion. Added a new cov...
Improved the efficiency of linear algebra calculations in GpRegressor related to hyper-parameter opt...
Fixed a bug in the ChangePoint covariance kernel which was causing GpRegressor to incorrectly assess...
Added a new method GpRegressor.gradient, which allows for the calculation of the mean and variance o...
Added a WhiteNoise covariance function to model the presence of Gaussian noise on input data for Gau...
GpRegressor now supports multi-start gradient-based hyper-parameter optimisation using the L-BFGS-B ...
Three new modules have been added to support the construction of likelihood, prior and posterior dis...
Improved numerical efficiency of the leapfrog update in HamiltonianChain. Fixed some errors so that ...
Added the HeteroscedasticNoise covariance kernel to the inference.covariance module, which allows fo...
Added a new module inference.approx for approximate inference tools. Currently contains the get_cond...
Pearson’s correlation coefficients and normalized root mean squared errors of GPR algorithm on CCHF ...
General New vignette Different Output between Stata and ggeffects. Changes to functions ggpr...
Fixed various bugs that appeared when testing after updating dependencies to numpy 1.15.0, scipy 1.3...
(rapidtide) Added new "--CVR" analysis type to generate calibrated CVR maps when given a CO2 regress...
Rather than assuming the mean of the Gaussian process is zero, GpRegressor now treats the mean as a ...
Added a new class GpLinearInverter for performing Gaussian-process linear inversion. Added a new cov...
Improved the efficiency of linear algebra calculations in GpRegressor related to hyper-parameter opt...
Fixed a bug in the ChangePoint covariance kernel which was causing GpRegressor to incorrectly assess...
Added a new method GpRegressor.gradient, which allows for the calculation of the mean and variance o...
Added a WhiteNoise covariance function to model the presence of Gaussian noise on input data for Gau...
GpRegressor now supports multi-start gradient-based hyper-parameter optimisation using the L-BFGS-B ...
Three new modules have been added to support the construction of likelihood, prior and posterior dis...
Improved numerical efficiency of the leapfrog update in HamiltonianChain. Fixed some errors so that ...
Added the HeteroscedasticNoise covariance kernel to the inference.covariance module, which allows fo...
Added a new module inference.approx for approximate inference tools. Currently contains the get_cond...
Pearson’s correlation coefficients and normalized root mean squared errors of GPR algorithm on CCHF ...
General New vignette Different Output between Stata and ggeffects. Changes to functions ggpr...
Fixed various bugs that appeared when testing after updating dependencies to numpy 1.15.0, scipy 1.3...
(rapidtide) Added new "--CVR" analysis type to generate calibrated CVR maps when given a CO2 regress...