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Going to try and add a set of default */lindsey.yaml configs for sweeping through the Lindsey et al results. Beyond just having those results on hand, it'll serve the purpose of having a set of simulations that's meant to stable. In contrast, the more generic classification.yaml experiment will adapt to enhancements and features to the library.
Develop and add */lindsey.yaml files.
Bonus points: See if we can implement a "SOTA" (e.g. alexnet) network on the scaled+shifted data, to provide a better performance upper bound on the task.
The text was updated successfully, but these errors were encountered:
bold move to call alexnet state of the art :D
Maybe also a ResNet (or ConvNext as the modernized version), perhaps even pretrained would give a more realistic upper bound
Going to try and add a set of default
*/lindsey.yaml
configs for sweeping through the Lindsey et al results. Beyond just having those results on hand, it'll serve the purpose of having a set of simulations that's meant to stable. In contrast, the more genericclassification.yaml
experiment will adapt to enhancements and features to the library.*/lindsey.yaml
files.The text was updated successfully, but these errors were encountered: