Background on variational models in Image Processing: including background theory, Total Variation Denoising, and Image Inpainting. Proof of convergence and generalization for Deep Neural Networks based on Lipschitz regularization.  Variational interpretation of Adversarial training (AT).  Adversarial robustness based on AT and Lipschitz regularization.