no code implementations • ICML 2020 • Li K. Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani
Models that employ latent variables to capture structure in observed data lie at the heart of many current unsupervised learning algorithms, but exact maximum-likelihood learning for powerful and flexible latent-variable models is almost always intractable.
no code implementations • 25 Sep 2019 • Sun Minni, Li Ji-An, Theodore Moskovitz, Grace Lindsay, Kenneth Miller, Mario Dipoppa, Guangyu Robert Yang
We found that neurons that project to higher-order areas will have greater stimulus selectivity, regardless of whether they are excitatory or not.
