This is the 4th in a series of panel discussions in collaboration with Neuromatch Academy, the online computational neuroscience summer school. This is the first of 3 in the deep learning series. In this episode, the panelists discuss their experiences with some basics in deep learning, including Linear deep learning, Pytorch, multi-layer-perceptrons, optimization, & regularization.
Support the show to get full episodes, full archive, and join the Discord community. Dean Buonomano runs the Buonomano lab at UCLA. Dean was...
Thomas and I discuss the role of recurrence in visual cognition: how brains somehow excel with so few “layers” compared to deep nets, how...
Chris and I discuss his Spaun large scale model of the human brain (Semantic Pointer Architecture Unified Network), as detailed in his book How...