CSSS 2010 Santa Fe-Readings: Difference between revisions
From Santa Fe Institute Events Wiki
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===Cosma Shalizi=== | ===Cosma Shalizi=== | ||
* [http://arxiv.org/abs/nlin.AO/0409024 Quantifying Self-Organization with Optimal Predictors]<br> | * [http://arxiv.org/abs/nlin.AO/0409024 Quantifying Self-Organization with Optimal Predictors]<br> | ||
* [http://arxiv.org/abs/nlin.AO/0307015 Methods and Techniques of Complex Systems Science: An Overview]<br> | * [http://arxiv.org/abs/nlin.AO/0307015 Methods and Techniques of Complex Systems Science: An Overview]<br> | ||
* [http://arxiv.org/abs/cs.LG/0406011 Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences]<br> | * [http://arxiv.org/abs/cs.LG/0406011 Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences]<br> | ||
* [http://arxiv.org/abs/nlin.CG/0508001 Automatic Filters for the Detection of Coherent Structure in Spatiotemporal Systems]<br> | * [http://arxiv.org/abs/nlin.CG/0508001 Automatic Filters for the Detection of Coherent Structure in Spatiotemporal Systems]<br> | ||
* [http://arxiv.org/abs/cond-mat/9907176 Computational Mechanics: Pattern and Prediction, Structure and Simplicity]<br> | |||
* [http://arxiv.org/abs/cond-mat/9907176 | |||
* [http://arxiv.org/abs/1001.0036 The Computational Structure of Spike Trains]<br> | * [http://arxiv.org/abs/1001.0036 The Computational Structure of Spike Trains]<br> | ||
* [http://arxiv.org/abs/q-bio.NC/0609008 Discovering Functional Communities in Dynamical Networks]<br> | * [http://arxiv.org/abs/q-bio.NC/0609008 Discovering Functional Communities in Dynamical Networks]<br> | ||
* [http://arxiv.org/abs/q-bio.NC/0506009 Measuring Shared Information and Coordinated Activity in Neuronal Networks]<br> | * [http://arxiv.org/abs/q-bio.NC/0506009 Measuring Shared Information and Coordinated Activity in Neuronal Networks]<br> | ||
* [http://arxiv.org/abs/math.PR/0305160 Optimal Nonlinear Prediction of Random Fields on Networks] | * [http://arxiv.org/abs/math.PR/0305160 Optimal Nonlinear Prediction of Random Fields on Networks] | ||
-------- | -------- | ||
[[Media:2010-06-15-info-theory.pdf|Information theory lecture slides]] | |||
[[Media:2010-06-15-optimal-prediction.pdf|Optimal prediction lecture slides]] | |||
[[Media:2010-06-16-complexity.pdf|Quantitative complex measures lecture slides]] | |||
=== Bill Croft, Ian Maddieson, Eric Smith=== | === Bill Croft, Ian Maddieson, Eric Smith=== | ||
Revision as of 19:34, 16 June 2010
| CSSS Santa Fe 2010 |
Please review readings before lectures. Supplemental material may be posted as well.
Background Readings
Please see the Background Readings page for assignments.
Dan Rockmore
Dan's Intro Lecture
Draft intro to stat learning primer
Tanmoy Bhattacharya
Inference in Historical Processes
Liz Bradley
- Numerical Solution of Differential Equations
- Time Series Analysis
- File:BradleySlides2010.pdf
- File:BradleySyllabus2010.pdf
Tom Carter
Here is a link to a page with various background readings -- I'll be talking about some of this material, watch the wiki for days/times
Iain Couzin
- Complexity. An Informative Itinerary
- Collective Cognition in Animal Groups
- Collective Motion and Cannibalism in Locust Migratory Bands
- Collective Minds
- Effective Leadership and Decision-Making in Animal Groups on the Move
Simon DeDeo
For the two lectures on "Physics of Reasoning" --
- E.T. Jaynes, Information Theory and Statistical Mechanics I.
- Gasper, Schneidman, Berry & Bialek, Ising models for networks of real neurons
- Reiss, Hammerich & Montroll, Thermodynamic treatment of nonphysical systems -- the off-site fulltext is available.
more advanced --
- Spin Glasses and Biology (ed. Daniel Stein) (available at SFI library)
- Park & Newman, Statistical Mechanics of Networks
- A.R. Liddle, How many cosmological parameters?
If you only have time to read one, read Jaynes! If you are unable to access any of these articles, feel free to e-mail me at simon@santafe.edu
Owen Densmore
Steve Guerin and I will present modeling with NetLogo. It will have two parts, one a self-paced wiki tutorial, the second a set of real world examples of modeling we've used professionally.
Read the first page of the tutorial. Then (attempt!) to download, install, and look at the Model Library.
Peter Dodds
Nathan Eagle
Doug Erwin
Duncan Foley
- Labor, Capital and Land in the New Economy
- Economic Complexity and Dynamics in Interactive Systems
- Hyman Minsky and the Dilemmas of Contemporary Economic Method
Laura Fortunato
Greg Leibon
John Harte
Jure Leskovec
1) -- models and link prediction in large social networks:
2) -- tracking information diffusion, finding influencers and detecting disease outbreaks in networks
- Meme Tracking & News Cycle Dynamics
- Maximizing the Spread of Influence through a Social Network
- Outbreak Detection in Social Networks
- 2004 Election Political Blogger Networks
3) -- models of networks with positive and negative ties
- Trust & Distrust
- Signed Networks & Social Media:
- Predicting Postive & Negative Links in Online Social Networks
- Governance in Social Media
Cosma Shalizi
- Quantifying Self-Organization with Optimal Predictors
- Methods and Techniques of Complex Systems Science: An Overview
- Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences
- Automatic Filters for the Detection of Coherent Structure in Spatiotemporal Systems
- Computational Mechanics: Pattern and Prediction, Structure and Simplicity
- The Computational Structure of Spike Trains
- Discovering Functional Communities in Dynamical Networks
- Measuring Shared Information and Coordinated Activity in Neuronal Networks
- Optimal Nonlinear Prediction of Random Fields on Networks
Information theory lecture slides
Optimal prediction lecture slides
Quantitative complex measures lecture slides
Bill Croft, Ian Maddieson, Eric Smith
Alfred Hübler
Scott Pauls
- Lecture on using the PDM on voting data.
- Code package
- Sample voting data