Explores machine learning models for neuroscience, focusing on understanding brain function and core object recognition through convolutional neural networks.
Covers the use of transformers in robotics, focusing on embodied perception and innovative applications in humanoid locomotion and reinforcement learning.
Explores perception in deep learning for autonomous vehicles, covering image classification, optimization methods, and the role of representation in machine learning.
