saxelab.org domain details

Example domain paragraphs

The interactions of billions of neurons ultimately give rise to our thoughts and actions. Remarkably, much of our behavior is learned starting in infancy and continuing throughout our lifespan. We aim to develop a mathematical toolkit suitable for analyzing and describing learning in the brain and mind. Our current focus is on the theory of deep learning, a class of artificial neural network models that take inspiration from the brain. Alongside this theoretical work, we develop close collaborations with ex

Selected publications

Saxe, A. M., McClelland, J. L., & Ganguli, S. (2019). A mathematical theory of semantic development in deep neural networks. Proceedings of the National Academy of Sciences , 116 (23), 11537–11546. https://doi.org/10.1073/pnas.1820226116 Abstract | arXiv | DOI An extensive body of empirical research has revealed remarkable regularities in the acquisition, organization, deployment, and neural representation of human semantic knowledge, thereby raising a fundamental conceptual question: What are the theoretic

Links to saxelab.org (3)

eringrant.github.io Erin Grant | Home
ucl-ellis.github.io UCL ELLIS
jinhl9.github.io Jin Hwa Lee