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Day 21 (8/5/19): Averaging Experiments

This morning I was at a basketball camp so I came into the lab around noon. Much of the day was spent waiting for some models to finish training to I worked on adding some slides to my presentation document.

In the afternoon, I got back results from models that I could average together to get more accurate results. The general trend remained the same however which indicated that the Mahalanobis Intra Dataset OOD actually performed better when it was trained incrementally (albeit with full rehearsal) than when it was trained offline. I am not sure yet what the reason for this is, but I will continue to look into it.
The green line denotes the intra dataset mahalanobis OOD omega for full rehearsal. Note how it consistently is above 1 even as more batches are learned incrementally.

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