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cs.LG2025
Optimal lower Lipschitz bounds for ReLU layers, saturation, and phase retrieval
Daniel Freeman, Daniel Haider
The injectivity of ReLU layers in neural networks, the recovery of vectors from clipped or saturated measurements, and (real) phase retrieval in allow for a similar…
cs.LG2024
(Almost) Smooth Sailing: Towards Numerical Stability of Neural Networks Through Differentiable Regularization of the Condition Number
Rossen Nenov, Daniel Haider, Peter Balazs
Maintaining numerical stability in machine learning models is crucial for their reliability and performance. One approach to maintain stability of a network layer is to integrate t…