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.
When a waiter hands me the bill, how do I know whether to pay it myself or let my date pay? On this episode,...
Support the show to get full episodes and join the Discord community. Doris, Tony, and Blake are the organizers for this year’s NAISys conference,...
Romain and I discuss his theoretical/philosophical work examining how neuroscientists rampantly misuse the word "code" when making claims about information processing in brains. We...
