Theoretical neuroscientists receive ENNS Best Paper Award at ICANN 2024
A team of theoretical neuroscientists has received the European Neural Network Society Best Paper Award at ICANN 2024, the 33rd International Conference on Artificial Neural Networks. The prestigious recognition was given for their paper “Biologically-plausible Markov Chain Monte Carlo Sampling from Vector Symbolic Algebra-encoded Distributions.”
Led by P. Michael Furlong, Research Officer at the NRC-UW Collaboration Centre, along with colleagues Kathryn Simone, Nicole Dumont, Madeleine Bartlett, Terrence Stewart and Professors Jeff Orchard and Chris Eliasmith, the work describes a way that a network of spiking neurons can generate random samples from a probability distribution. The distribution is encoded using vector symbolic algebra, a type of compositional language embedded in a vector space.
