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.
Support the show to get full episodes and join the Discord community. Check out my free video series about what's missing in AI and...
BI NMA 05: NLP and Generative Models Panel This is the 5th in a series of panel discussions in collaboration with Neuromatch Academy, the...
Show notes: Follow Dean on Twitter: @deanbuonoVisit his lab website at UCLA.The review we discuss: The Neural Basis of Timing: Distributed Mechanisms for Diverse...
