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Difference between revisions of "Randomness, Structure and Causality - Participants"

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<td>nay@mis.mpg.de</td>
<td>nay@mis.mpg.de</td>
<td>SFI & Max Planck Institute</td>
<td>SFI & Max Planck Institute</td>
<td>Effective Complexity of Stationary Process Realizations</td>
<td>A Geometric Approach to Complexity</td>
<td>[[http://arxiv.org/abs/1001.2686]]</td>
<td>[[http://arxiv.org/abs/1001.2686]]</td>
</tr>
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</tr>
</tr>
<tr>
<tr>
<td>Bergstrom, Carl</td>
<td>*Bettencourt, Luis</td>
<td>cbergst@u.washington.edu</td>
<td>lmbettencourt@gmail.com</td>
<td>SFI & University of Washington</td>
<td>SFI & LANL</td>
<td>The Transmission Sense of Information</td>
<td>Information Aggregation in Correlated Complex Systems and Optimal Estimation</td>
<td>[[http://arxiv.org/abs/0810.4168]]</td>
<td>[[http://arxiv.org/abs/0712.2218]]</td>
</tr>
<tr>
<td>Bialek, William</td>
<td>wbialek@Princeton.EDU</td>
<td>Princeton University</td>
<td>Optimizing Information Flow in Small Genetic Networks</td>
<td>[[http://arxiv.org/abs/0912.5500]]</td>
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<td>IBM Watson Research Center</td>
<td>IBM Watson Research Center</td>
<td>To a Mathematical Theory of Evolution and Biological Creativity</td>
<td>To a Mathematical Theory of Evolution and Biological Creativity</td>
<td>[[File:Darwin.pdf]]</td>
<td>[[Media:Darwin.pdf| Paper]]</td>
</tr>
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<td>College of the Atlantic</td>
<td>College of the Atlantic</td>
<td>Complexity Measures and Frustration</td>
<td>Complexity Measures and Frustration</td>
<td>[[File:afm.tri.5.pdf]] and [[File:CHAOEH184043106_1.pdf]] </td>
<td>[[Media:afm.tri.5.pdf| Paper 1]] and [[Media:CHAOEH184043106_1.pdf| Paper 2]] </td>
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<td>SFI & University of New Mexico</td>
<td>SFI & University of New Mexico</td>
<td>Phase Transitions and Computational Complexity</td>
<td>Phase Transitions and Computational Complexity</td>
<td></td>
</tr>
<tr>
<td>*Shaw, Robert Stetson</td>
<td>rob@protolife.net</td>
<td>ProtoLife, Inc.</td>
<td>Dominos, Ergodic Flows</td>
<td></td>
<td></td>
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<td>University of Hawaii at Manoa</td>
<td>University of Hawaii at Manoa</td>
<td>Statistical Mechanics of Interactive Learning</td>
<td>Statistical Mechanics of Interactive Learning</td>
<td></td>
</tr>
<tr>
<td>Tononi, Guilio</td>
<td>gtononi@wisc.edu</td>
<td>University of Michigan</td>
<td>Measuring the Complexity of Psychological States </td>
<td></td>
<td></td>
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</tr>

Latest revision as of 00:49, 9 January 2011

Workshop Navigation


Name Email Institution Talk Paper
*Ay, Nihat nay@mis.mpg.de SFI & Max Planck Institute A Geometric Approach to Complexity [[1]]
*Bell, Tony tony@salk.edu UC Berkeley Learning Out of Equilibrium
*Bettencourt, Luis lmbettencourt@gmail.com SFI & LANL Information Aggregation in Correlated Complex Systems and Optimal Estimation [[2]]
*Chaitin, Gregory gjchaitin@gmail.com IBM Watson Research Center To a Mathematical Theory of Evolution and Biological Creativity Paper
*Crutchfield, James chaos@cse.ucdavis.edu SFI & UC Davis Framing Complexity [[3]]
*Debowski, Lukasz ldebowsk@ipipan.waw.pl Polish Academy of Sciences The Vocabulary of Grammar-Based Codes and the Logical Consistency of Texts [[4]] and [[5]]
*Ellison, Christopher cellison@cse.ucdavis.edu UC Davis Prediction, Retrodiction, and the Amount of Information Stored in the Present [[6]]
*Feldman, David dave@hornacek.coa.edu College of the Atlantic Complexity Measures and Frustration Paper 1 and Paper 2
*Mahoney, John jmahoney3@ucmerced.edu UC Merced Crypticity and Information Accessibility [[7]]
*Machta, Jon machta@physics.umass.edu SFI & University of Massachusetts Complexity, Parallel Computation and Statistical Physics [[8]]
*Mitchell, Melanie mm@cs.pdx.edu SFI & Portland State University Automatic Identification of Information-Processing Structures in Cellular Automata
*Moore, Cris moore@cs.unm SFI & University of New Mexico Phase Transitions and Computational Complexity
*Shaw, Robert Stetson rob@protolife.net ProtoLife, Inc. Dominos, Ergodic Flows
*Still, Suzanne sstill@hawaii.edu University of Hawaii at Manoa Statistical Mechanics of Interactive Learning
*Vilela-Mendes, Rui vilela@cii.fc.ul.pt University of Lisbon Ergodic Parameters and Dynamical Complexity [[9]]
Trabesinger, Andreas a.trabesinger@nature.com Nature Physics Magazine Measuring Complexity? [[10]]
*Wiesner, Karoline k.wiesner@bristol.ac.uk University of Bristol Hidden Quantum Markov Models and Non-adaptive Read-out of Many-body States [[11]]

*Confirmed