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Found 5 papers, 1 papers with code
CGDTest: A Constrained Gradient Descent Algorithm for Testing Neural Networks
This functionality sets CGDTest apart from other similar DNN testing tools since it allows users to specify logical constraints to test DNNs not only for $\ell_p$ ball-based adversarial robustness but, more importantly, includes richer properties such as disguised and flow adversarial constraints, as well as adversarial robustness in the NLP domain.
GANs & Reels: Creating Irish Music using a Generative Adversarial Network
In this paper we present a method for algorithmic melody generation using a generative adversarial network without recurrent components.
Amnesiac Machine Learning
In this paper, we present two efficient methods that address this question of how a model owner or data holder may delete personal data from models in such a way that they may not be vulnerable to model inversion and membership inference attacks while maintaining model efficacy.
xAI-GAN: Enhancing Generative Adversarial Networks via Explainable AI Systems
A potential weakness in GANs is that it requires a lot of data for successful training and data collection can be an expensive process.
Non-Sequential Melody Generation
In this paper we present a method for algorithmic melody generation using a generative adversarial network without recurrent components.
