 | Panelist: Redwood Center for Theoretical Neuroscience, UCB Anthony J. Bell Ph.D. Redwood Center for Theoretical Neuroscience UC Berkeley My interest in 2007 is:- To unify ideas from probabilistic unsupervised machine learning with the cross-level information flows that occur in the biological hierarchy. The idea is that macroscopic variables can use microscopic variables to store information. You might not realise it but this sentence you are reading is changing your gene expression (your genes heard it here first!) I am demonstrating this concept with new learning algorithms, focusing on synaptic learning phenomena such as spike timing-dependent plasticity (STDP), and on systems of kinetic equations inspired by the processes that govern the flow of information inside a cell (for example ion channel and enzyme kinetics). In the process, I am creating dynamic signal processing algorithms with new properties. I hope they will be powerful. I know this requires some explanation. I need to completely revamp my web-presence, and I hope to do so soon, along with papers explaining this idea. My old page, at the Salk Institute, is quite out-of-date, but contains some useful material. http://redwood.berkeley.edu/wiki/Tony_Bell |
العربية
中国
Français
Deutsch
Ελληνική
हिन्दी
Italiano
日本語
Português
Русский
Español
