Biologically Plausible Neural Networks

 Great discussion with Simon Stringer from the Oxford Center for Theoretical Neuroscience and Artificial Intelligence.  Pay special attention to the discussion of the 'feature binding' problem.  If you are a computer artist, think about Gestalt principles when he's talking about this. How the theoretical models work off of streams of varying images (from saccades) is also fascinating, and should get you thinking about data augmentation.

The conversation includes a discussion of the emergence of self-organized behavior, complex information processing, invariant sensory representations and hierarchical feature binding which emerges when you build biologically plausible neural networks with temporal spiking dynamics.


Here's a link to the paper 'A new approach to solving the feature-binding problem in primate visions'.

Here's a link to Simon's research page if you want to learn more about his research.

Comments

Post a Comment

Popular posts from this blog

CycleGAN: a GAN architecture for learning unpaired image to image transformations

Pix2Pix: a GAN architecture for image to image transformation

Smart Fabrics