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.
In this second part of our conversation David, John, and I continue to discuss the role of complexity science in the study of intelligence,...
Support the show to get full episodes and join the Discord community. Mike and I discuss his modeling approach to study cognition. Many people...
[bctt tweet="Check out episode 6 of the Brain Inspired podcast: Deep learning, eyeballs, and brains" username="pgmid"] Mentioned in the show Ryan Poplin What is...
