Model Compression and Deployment
The model is the easy part. Everything after training is where deployments fail.
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Adversarial Robustness in Deep Learning
A change too small to see can flip a classifier’s answer. That is a property of the models, not a bug in one of them.
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Uncertainty Estimation and Model Calibration
A softmax output of 0.99 is not a 99% chance of being right. Here is how far apart those two things are.
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Deep Learning Interpretability
A model that is right for the wrong reason will fail the moment the reason changes.