Delves into adversarial machine learning, exploring small perturbations causing misclassifications in neural networks and the trade-off between accuracy and robustness.

Adversarial Machine Learning

Delves into adversarial machine learning, exploring optimization formulations and robustness examples.

Non-Conceptual Knowledge Systems: Style Transfer and Image Translation

Explores style transfer, image translation, self-supervised learning, video prediction, and image description generation using deep learning techniques.

Adversarial Machine Learning: Fundamentals and Techniques

Explores adversarial machine learning, covering the generation of adversarial examples, robustness challenges, and techniques like Fast Gradient Sign Method.

Deep Learning: Convolutional Neural Networks

Covers Convolutional Neural Networks, standard architectures, training techniques, and adversarial examples in deep learning.

Adversarial Machine Learning

Explore the vulnerabilities of neural networks to adversarial attacks and the strategies to enhance model robustness.

Deep Learning Agents: Reinforcement Learning

Explores Deep Learning Agents in Reinforcement Learning, emphasizing neural network approximations and challenges in training multiagent systems.

Non-Conceptual Knowledge Systems

Delves into the impact of deep learning on non-conceptual knowledge systems and the advancements in transformers and generative adversarial networks.