Using relativism to improve GAN-based Adversarial Attacks. 🦾

Fully Connected Neural Networks, Multilayer Neural Networks, MAdaline, CNNs, Segmentation, Detection, RNNs, CNN-LSTM, LSTM, Bi-LSTM, GRU, Transformers, Huber Loss, ViT, DGMs, Triplet VAE, AdvGAN, Image Caption Generation, attention, LLM Fine-Tuning, Soft Prompting, LoRA, Layer Freezing, SlimOrca

B.Sc. Final Project: Generating adversarial examples using GAN (Generative Adversarial Network) in Pytorch on the MNIST dataset.