A single-weight perturbation at the very start of training makes otherwise identical neural networks diverge to different loss basins, and this sensitivity drops sharply within the first fraction of training.
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The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions
A single-weight perturbation at the very start of training makes otherwise identical neural networks diverge to different loss basins, and this sensitivity drops sharply within the first fraction of training.