In this second part of my discussion with Wolfgang (check out the first part), we talk about spiking neural networks in general, principles of brain computation he finds promising for implementing better network models, and we quickly overview some of his recent work on using these principles to build models with biologically plausible learning mechanisms, a spiking network analog of the well-known LSTM recurrent network, and meta-learning using reservoir computing.
David and John discuss some of the concepts from their recent paper Two Views on the Cognitive Brain, in which they argue the recent...
Grace’s websiteTwitter: @neurograce.Models of the Mind: How Physics, Engineering and Mathematics Have Shaped Our Understanding of the Brain.We talked about Grace’s work using convolutional...
Jay's homepage at Stanford.Implementing mathematical reasoning in machines:The video lecture.The paper.Parallel Distributed Processing by Rumelhart and McClelland.Complimentary Learning Systems Theory and Its Recent Update.Episode...
