Neuro-Inspired Topology and Machine Learning

Mathematics, machine learning, and computational neuroscience have long been intertwined. Mathematical tools such as graph theory, information theory and dynamical systems have been used to model neural activity. Similarly, modern machine learning approaches have been inspired by neuroscience and have been used to better understand brain connectivity and dynamics. These three research facets play off of each other to advance each field individually and concurrently. The goal of this workshop is to bring computational neuroscientists, mathematicians, and computer scientists together to communicate research around their expertise. Additionally, it will serve as a venue to discuss avenues of future research impacting computational neuroscience and mathematics while advancing machine learning and artificial intelligence methods.

Note, this workshop is being held in conjunction with CNS 2023. Full conference schedule can be found here.