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As we are adding more contrasts and re-training the model overtime (see eg: #83, #74, ivadomed/canproco#46), we need to put in place a quality check assessment of model performance shift across various data domains (ie: monitor catastrophic forgetting).
The text was updated successfully, but these errors were encountered:
A relevant theory paper I found: Understanding Continual Learning Settings with Data Distribution Drift Analysis -- Essentially describes the theory of data distribution shifts, proposes new concepts in analyzing model/data drifts and some of the existing concepts in lifelong learning that are related to this phenomenon.
Relevant sections: Sections 3.1, 3.2, 4.1, and 6.2
As we are adding more contrasts and re-training the model overtime (see eg: #83, #74, ivadomed/canproco#46), we need to put in place a quality check assessment of model performance shift across various data domains (ie: monitor catastrophic forgetting).
The text was updated successfully, but these errors were encountered: