COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |
University of Cambridge > Talks.cam > Computational Neuroscience > Single-phase deep learning in cortico-cortical networks
Single-phase deep learning in cortico-cortical networksAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Samuel Eckmann. This talk has been canceled/deleted Introducing a new model, Bursting Cortico-Cortical Networks (BurstCCN), that is capable of backpropagation-like learning using biologically plausible mechanisms. Importantly, unlike previous work, the BurstCCN can learn complex tasks with high accuracy without requiring an implausible two-phase learning process. This talk is part of the Computational Neuroscience series. This talk is included in these lists:This talk is not included in any other list Note that ex-directory lists are not shown. |
Other listsType the title of a new list here Philiminality Communications Research Group SeminarOther talksNew Technologies for the Synthesis, Semi-Synthesis and Biosynthesis of Modified Peptides and Proteins Machine Learning Solutions to the Yang Baxter Equation Polynomial Chaos Expansions - Basics Why ants need antennas PCE - Model Error Second-order modifications of gravity |