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Found 3 papers, 2 papers with code
GraN-GAN: Piecewise Gradient Normalization for Generative Adversarial Networks
Under such a class of discriminator (or critic) functions, we present Gradient Normalization (GraN), a novel input-dependent normalization method, which guarantees a piecewise K-Lipschitz constraint in the input space.
Exploiting Uncertainty of Loss Landscape for Stochastic Optimization
We introduce novel variants of momentum by incorporating the variance of the stochastic loss function.
Emulating malware authors for proactive protection using GANs over a distributed image visualization of dynamic file behavior
The GAN is trained over a reversible distributed RGB image representation of known malware behaviors, encoding the sequence of API call ngrams and the corresponding term frequencies.
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