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Introducing quad
acquisition functions
#749
Merged
mmahsereci
merged 15 commits into
probabilistic-numerics:main
from
mmahsereci:mm-quad-acquisition
Dec 14, 2022
Merged
Introducing quad
acquisition functions
#749
mmahsereci
merged 15 commits into
probabilistic-numerics:main
from
mmahsereci:mm-quad-acquisition
Dec 14, 2022
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Codecov Report
@@ Coverage Diff @@
## main #749 +/- ##
==========================================
+ Coverage 90.71% 90.79% +0.07%
==========================================
Files 206 210 +4
Lines 7638 7703 +65
Branches 982 986 +4
==========================================
+ Hits 6929 6994 +65
Misses 478 478
Partials 231 231
|
tskarvone
reviewed
Dec 13, 2022
src/probnum/quad/solvers/acquisition_functions/_predictive_variance.py
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tskarvone
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Dec 14, 2022
tskarvone
approved these changes
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In a Nutshell
This PR introduces acquisition functions to the
quad
package. Since there are no gradients yet, the corresponding policy samples random candidates and returns the one with the highest acquisition value. It will be straightforward to add a policy that uses a gradient-based optimizer once gradients are available.Detailed Description
BQState
got augmented with the cholesky of the gram matrix.Should be reviewed after #748 is merged as it branches off of it.Related Issues
Closes #...