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Found 5 papers, 3 papers with code
DAFA: Distance-Aware Fair Adversarial Training
The disparity in accuracy between classes in standard training is amplified during adversarial training, a phenomenon termed the robust fairness problem.
New Insights for the Stability-Plasticity Dilemma in Online Continual Learning
The aim of continual learning is to learn new tasks continuously (i. e., plasticity) without forgetting previously learned knowledge from old tasks (i. e., stability).
Stein Latent Optimization for Generative Adversarial Networks
Generative adversarial networks (GANs) with clustered latent spaces can perform conditional generation in a completely unsupervised manner.
PuVAE: A Variational Autoencoder to Purify Adversarial Examples
Deep neural networks are widely used and exhibit excellent performance in many areas.
Ranked #2 on
Adversarial Defense against FGSM Attack
on MNIST
Security and Privacy Issues in Deep Learning
Furthermore, the privacy of the data involved in model training is also threatened by attacks such as the model-inversion attack, or by dishonest service providers of AI applications.
