-
**Submitting author:** @davidogara (David O’Gara)
**Repository:** https://github.com/davidogara/hetGPy
**Branch with paper.md** (empty if default branch):
**Version:** v1.1
**Editor:** @matthewfeicke…
-
Hi there,
I am interested in Implementing a Dirichlet process mixture of Gaussian processes in matlab. I have my data set which is 57X3 where the format is [Latitude,Longitude,Probability] and I have …
-
In the long term, it would be nice if one could `tell` a pair `(x, y)` along with uncertainty on `y`.
For example, when `y` is a cross-validation estimate of the performance of a ML model parameter…
-
Since yesterday I get the following error when running nnU-net v2.4.2 on windows. On ubuntu and mac this error does not happen. On windows this error also did not happen 3 days ago. Probably there was…
-
Hi,
In the active learning for regression example, we have used gaussian processes. While the sklearn version seems to keep its length scale and noise parameters static ( maybe i am doing something…
-
_The following peer review was solicited as part of the Distill review process._
_**The reviewer chose to waive anonymity.** Distill offers reviewers a choice between anonymous review and offering …
-
Hi,
When trying to generate molecular descriptors for molecules in different solvents, the input generator generates gaussian inputs with a name that is the inchikey and the conformation index. Thus,…
-
We can perform QM/pol-MM calculations using Gaussian for QM part calculation and Tinker for MM part calculation. I just have a doubt:
How does the MM part respond to the QM part for a self-consistent…
-
Montblanc currently only predicts from delta functions, 2D Gaussians and Sersic functions. It should be possible to predict from arbitrary functions by computing the Fourier transform of a Gaussian pr…
-
**Summary**
'mmrm' already supports 'spatial' covariance structures. These are essentially covariance functions and allow fitting Gaussian process models.
GP models are particularly useful whe…