Neural computation and learning. Discussions of classic as well as recent papers in neural computing and neuroscience. Participants select one or more papers from a reading list and will lead the corresponding discussion meetings. Specific topics covered include:

Supervised and unsupervised learning

Reinforcement learning and imitation learning

Bayesian inference and relationship to neural networks

Recurrent and hierarchical networks

Applications in computer vision, robotics, and brain-computer interfaces