I am a Cognitive Science PhD student at UCSD studying the computational basis of social cognition and communication. In the past, I’ve worked in industry in NLP & computational linguistics and at MIT on autonomous vehicles.
Brains are comprised of networks of neurons connected by synapses, and these networks have greater computational properties than the neurons and synapses themselves. In this post, I am going to talk about a class of neural networks which I think are fascinating: attractor networks. These are recurrent neural networks with attractor states; these states and … Continue reading “Attractor Networks, (A bit of) Computational Neuroscience Part III”