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Arthur Douillard
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[info] Remove initial results.
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README.md

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@@ -16,34 +16,9 @@ Every model must inherit `inclearn.models.base.IncrementalLearner`.
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:white_check_mark: iCaRL\
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:construction: Learning without Forgetting (LwF)\
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:white_check_mark: End-to-End Incremental Learning (E2E)
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:white_check_mark: End-to-End Incremental Learning (E2E)\
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:x: Overcoming catastrophic forgetting (EWC)
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## Results
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Every experiments have been runned at least 20 times, each with a different class
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ordering. The class ordering is defined by random using a different seed. I'm
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using the seed from 1 to 20.
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```bash
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python3 inclearn --model <model> --seed-range 1 20 --name <exp_name> <other options>
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```
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The metric used is what iCaRL defined the `average incremental accuracy`. It's
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what is plotted on every graph. In addition the in-parenthesis metric is the
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average of those average incremental accuracy. You can see in the notebook
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[here](results.ipynb) how it is done.
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I'll always precise whether the results are from a paper `[paper]` or myself `[me]`.
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### iCIFAR100, 10-split
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![icifar100, 10 split](figures/icifar100_10split.png)
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### iCIFAR100, 2-split
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TODO
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## TODO

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