Tony Bell: Difference between revisions

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[[Image:tony.jpg|150px|left]]  
[[Image:tony.jpg|150px|left]]  
Friedrich T. Sommer, Ph.D. <br />
Anthony J. Bell Ph.D. <br />
Redwood Center for Theoretical Neuroscience <br />
Redwood Center for Theoretical Neuroscience <br />
UC Berkeley <br />
UC Berkeley <br />
132 Barker, MC #3190 <br />
132 Barker, MC #3190 <br />
Berkeley, CA 94720-3190 <br />
Berkeley, CA 94720-3190 <br />
phone (510) 643-1472 <br />
phone (415) 699 6502 <br />
fax (510) 643-4952 <br />
fax (510) 643-4952 <br />
<fsommer at berkeley dot edu><br />
<tbell at berkeley dot edu><br />
<br style="clear:both;" />
<br style="clear:both;" />


Associate Adjunct Professor, Redwood Center for Theoretical Neuroscience & Helen Wills Neuroscience Institute, University of California, Berkeley <br />
== Research Interests ==
Faculty member (Hochschuldozent), Department of Computer Science, University of Ulm


----
My current interests are:-


(1) to unify ideas from probabilistic machine learning
with the cross-level information flows that occur in the biological hierarchy.
The test-case is to explain synaptic, dendritic and axonal learning as an
information flow between neurons and synapses


(2) to develop simple algorithms that capture the statistical structure of
multivariate signals


== Research Interests ==
I know this requires some explanation. At some later date, I will embellish
 
this page and add the publications.
Many impressive capabilities of the brain

Revision as of 00:36, 5 October 2006

Tony.jpg

Anthony J. Bell Ph.D.
Redwood Center for Theoretical Neuroscience
UC Berkeley
132 Barker, MC #3190
Berkeley, CA 94720-3190
phone (415) 699 6502
fax (510) 643-4952
<tbell at berkeley dot edu>

Research Interests

My current interests are:-

(1) to unify ideas from probabilistic machine learning with the cross-level information flows that occur in the biological hierarchy. The test-case is to explain synaptic, dendritic and axonal learning as an information flow between neurons and synapses

(2) to develop simple algorithms that capture the statistical structure of multivariate signals

I know this requires some explanation. At some later date, I will embellish this page and add the publications.