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.
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Support the show to get full episodes, full archive, and join the Discord community. The Transmitter is an online publication that aims to deliver...
Sanjeev and I discuss some of the progress toward understanding how deep learning works, specially under previous assumptions it wouldn’t or shouldn’t work as...
