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LatentKroneckerGP
for Learning Curve Prediction
#2633
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This pull request was exported from Phabricator. Differential Revision: D66158880 |
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #2633 +/- ##
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- Coverage 99.98% 99.98% -0.01%
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Files 198 200 +2
Lines 17910 18149 +239
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+ Hits 17908 18146 +238
- Misses 2 3 +1 ☔ View full report in Codecov by Sentry. |
Summary: Pull Request resolved: pytorch#2633 The `LatentKroneckerGP` model for joint learning curve and hyper-parameter modeling in AutoML. See [Lin et al. 2024](https://arxiv.org/abs/2410.09239). Differential Revision: D66158880
This pull request was exported from Phabricator. Differential Revision: D66158880 |
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Summary: Pull Request resolved: pytorch#2633 The `LatentKroneckerGP` model for joint learning curve and hyper-parameter modeling in AutoML. See [Lin et al. 2024](https://arxiv.org/abs/2410.09239). Differential Revision: D66158880
Summary: Pull Request resolved: pytorch#2647 Pull Request resolved: pytorch#2633 The `LatentKroneckerGP` model for joint learning curve and hyper-parameter modeling in AutoML. See [Lin et al. 2024](https://arxiv.org/abs/2410.09239). Reviewed By: Balandat Differential Revision: D66158880
Summary: Pull Request resolved: pytorch#2647 Pull Request resolved: pytorch#2633 The `LatentKroneckerGP` model for joint learning curve and hyper-parameter modeling in AutoML. See [Lin et al. 2024](https://arxiv.org/abs/2410.09239). Reviewed By: Balandat Differential Revision: D66158880
Summary: The
LatentKroneckerGP
model for joint learning curve and hyper-parameter modeling in AutoML. See Lin et al. 2024.Implemented by @jandylin.
Differential Revision: D66158880