Comparing high-dimensional neural distributions with computational geometry and optimal transport 

Mathematical Biology Seminar
Wednesday, November 20, 2019 - 11:00am for 1 hour (actually 50 minutes)
Skiles 006
Eva Dyer – Georgia Tech (BME & ECE)
Christine Heitsch

In both biological brains and artificial neural networks, the representational geometry - the shape and distribution of activity - at different layers in an artificial network or across different populations of neurons in the brain, can reveal important signatures of the underlying computations taking place. In this talk, I will describe how we are developing strategies for comparing and aligning neural representations, using a combination of tools from computational geometry and optimal transport.