Graduate Summer School: Probabilistic Models of Cognition: The Mathematics of Mind - IPAM

Graduate Summer School: Probabilistic Models of Cognition: The Mathematics of Mind

July 9 - 26, 2007

Schedule

All times in this Schedule are Pacific Time (PT)

Monday, July 9, 2007

Morning Session

08:00-08:45
Check-in & Continental Breakfast
08:45-09:00
Introductory Remarks
09:00-10:00
Josh Tenenbaum (Massachusetts Institute of Technology)
Introduction to Probabilistic Models of Cognition
10:00-10:15
Break
10:15-11:15
Josh Tenenbaum (Massachusetts Institute of Technology)
Basic Bayes: model fitting, model selection, and model averaging
11:15-11:30
Break
11:30-12:30
Nick Chater (University College London)
From deduction and symbols to induction and probabilities

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45-14:45
Tom Griffiths (University of California, Berkeley (UC Berkeley))
Introduction to Graphical Models
15:00-16:00
Robert Jacobs (University of Rochester)
Bayesian Decision Theory
16:00-16:30
Break
16:30-17:30
Ying Nian Wu (University of California, Los Angeles (UCLA))
Information Theory
17:30-19:00
Opening Reception hosted by IPAM (IPAM Building)
19:00
*Optional Evening Session - Nick Chater, Tom Griffiths, Josh Tenenbaum, "Subjective probability and Bayesian foundations"

Matlab tutorial, by Amy Perfors

Tuesday, July 10, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:00
Alan Yuille (University of California, Los Angeles (UCLA))
Graphical Models in Vision
10:00-10:15
Break
10:15-11:15
Alan Yuille (University of California, Los Angeles (UCLA))
HMMs and inference in graphical models I
11:15-11:30
Break
11:30-12:30
Robert Jacobs (University of Rochester)
Ideal Observers and Ideal Actors

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45-14:45
Hongjing Lu (University of California, Los Angeles (UCLA))
Comparisons between human performance and model predictions in motion perception
15:00-16:00
Alan Yuille (University of California, Los Angeles (UCLA))
HMMs and inference in graphical models II
16:00-16:30
Break
16:30-17:30
Robert Jacobs (University of Rochester)
Sensory Cue Combination
19:00
*Optional Evening Session - Introduction to software for Bayesian modeling: SamIAm, Bayes Net Toolbox (BNT)

Wednesday, July 11, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:00
Zoubin Ghahramani (University of Cambridge)
Probabilistic generative models and unsupervised learning I
10:00-10:15
Break
10:15-11:15
Zoubin Ghahramani (University of Cambridge)
Probabilistic generative models and unsupervised learning II
11:15-11:30
Break
11:30-12:30
Zoubin Ghahramani (University of Cambridge)
Nonparametric Bayesian Models

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45-14:45
Breakout Session

Zoubin Ghahramani
Questions on generative models and nonparametric Bayes
15:00-16:00
Tom Griffiths (University of California, Berkeley (UC Berkeley))
Modern Monte Carlo methods I: Importance sampling and sequential Monte Carlo
16:00-16:30
Break
16:30-17:30
Tom Griffiths (University of California, Berkeley (UC Berkeley))
Modern Monte Carlo methods II: Markov chain Monte Carlo
19:00
*Optional Evening Session - Nick Chater, "Scale invariance in human cognition"
PowerPoint Presentation

Thursday, July 12, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:30
Zoubin Ghahramani (University of Cambridge)
Bayesian supervised learning and semi-supervised learning
10:30-11:00
Break
11:00-12:30
Ying Nian Wu (University of California, Los Angeles (UCLA))
Hierarchical Bayesian Models

Afternoon Session

12:30-13:30
Lunch (on your own)

Charles Kemp, Amy Perfors, Josh Tenenbaum
Learning overhypotheses with hierarchical Bayesian models
13:45-14:45
Breakout Sessions

Zoubin Ghahramani, Yingnian Wu
Technical questions on Bayesian models

Tom Griffiths
MCMC with humans, and other questions on MCMC

"Practical experiments with simple Bayesian models", Amy Perfors
15:00-16:15
Josh Tenenbaum (Massachusetts Institute of Technology)
Hierarchical Bayesian models of human inductive learning
16:15-16:30
Break
16:30-17:30
Nick Chater (University College London)
Information theory, minimum description length, and human cognition
19:00
*Optional Evening Session - Michael Lee, "Bayesian model theoretics and BUGS"

Friday, July 13, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-09:45
Ying Nian Wu (University of California, Los Angeles (UCLA))
Causal Models
09:50-10:45
Tom Griffiths (University of California, Berkeley (UC Berkeley))
Graphical models and human causal learning
10:45-11:15
Break
11:15-12:00
Hongjing Lu (University of California, Los Angeles (UCLA))
Model selection versus parameter estimation in Bayesian inference: An application to causal learning

Afternoon Session

12:05-12:50
Patricia Cheng (University of California, Los Angeles (UCLA))
Causal Reasoning in Humans and Rats
12:50-2:00
Lunch (on your own)

Breakout Sessions

Ed Vul
"Bayes Net Toolbox causal model demo"
14:00-15:00
Alison Gopnik (University of California, Berkeley (UC Berkeley))
Causal Learning in Children
15:15-16:00
Tom Griffiths (University of California, Berkeley (UC Berkeley))
Modeling causal learning in children
16:00-16:30
Break
16:30-17:30
Keith Holyoak (University of California, Los Angeles (UCLA))
From Causal Models to Analogical Inference

Monday, July 16, 2007

Morning Session

08:00-09:00
Check-in & Continental Breakfast
09:00-10:00
Stuart Russell (University of California, Berkeley (UC Berkeley))
Probability for Worlds with Things in Them
10:00-10:15
Break
10:15-11:15
Brian Milch (Google Inc.)
Relational Probability Models
11:15-11:30
Break
11:30-12:30
Brian Milch (Google Inc.)
Unknown Objects and BLOG

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45-14:45
Breakout Sessions

Stuart Russell, Brian Milch
Questions on first-order probability and BLOG
15:00-16:00
Josh Tenenbaum (Massachusetts Institute of Technology)
First-order probabilistic models in human cognition
16:00-16:30
Break
16:30-17:30
Charles Kemp (Massachusetts Institute of Technology)
Learning relational theories
19:00
*Optional Evening Session - Stanley Kok, Markov Logic Networks (MLNs) and the Alchemy system
Presentation (PowerPoint)

Tuesday, July 17, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:00
Stuart Geman (Brown University)
Hierarchy and Reusability in Image Analysis I
10:00-10:15
Break
10:15-11:15
Stuart Geman (Brown University)
Hierarchy and Reusability in Image Analysis II
11:15-11:30
Break
11:30-12:30
Alan Yuille (University of California, Los Angeles (UCLA))
Image Parsing

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45-14:45
Breakout Session

Stuart Geman/Alan Yuille
Questions on grammars for image parsing

Stanley Kok
Questions on MLNs and Alchemy
15:00-16:00
Fei-Fei Li (Princeton University)
Discovering Meaning in the Visual World
16:00-16:30
Break
16:30-17:30
Dan Kersten (University of Minnesota, Twin Cities)
Human Object Perception: Bottom-up and Top-down
19:00
*Optional Evening Session: Stuart Russell, Brian Milch, Josh Tenenbaum, Charles Kemp, et al: Discussion on connections between Cognitive Science and AI.

Wednesday, July 18, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:00
Mark Johnson (Brown University)
An introduction to grammars and parsing for language 1
10:00-10:15
Break
10:15-11:15
Mark Johnson (Brown University)
An introduction to grammars and parsing for language 2<br>Updated Presentation
11:15-11:30
Break
11:30-12:30
Roger Levy (University of California, San Diego (UCSD))
Probabilistic sentence processing 1

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45-14:45
Breakout Session

Roger Levy, Mark Johnson
Questions on grammars for language, and connections between human and machine language research

Noah Goodman
Probabilistic grammars for concept learning
15:00-16:00
Roger Levy (University of California, San Diego (UCSD))
Probabilistic sentence processing 2
16:00-16:30
Break
16:30-17:30
Mark Steyvers (University of California, Irvine (UCI))
Semantic Representations with Probabilistic Topic Models
17:30-19:00
Reception hosted by IPAM (IPAM Building)

Thursday, July 19, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:00
Peter Dayan (University College London)
Models of conditioning
10:00-10:15
Break
10:15-11:15
John Kruschke (Indiana University)
Locally Bayesian Learning
11:15-11:30
Break
11:30-12:30
Nathaniel Daw (New York University)
Advanced conditioning: competition and graphical models

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45-14:45
Breakout Session

Stuart Russell, Peter Dayan
Questions and dialog on reinforcement learning
15:00-16:00
Stuart Russell (University of California, Berkeley (UC Berkeley))
Reinforcement Learning
16:00-16:30
Break
16:30-17:30
Angela Yu (Princeton University)
Bayesian Decision Theory and Sequential Sampling

Friday, July 20, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:00
Bernard Balleine (UCLA)
Neural Substrates for Conditioning
10:00-10:15
Break
10:15-11:15
Peter Dayan (University College London)
Neural representation of value, reward and expectation
11:15-11:30
Break
11:30-12:30
Nathaniel Daw (New York University)
Reinforcement learning in human neuroimaging; uncertainty-based competition

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45-14:45
Breakout Session

Peter Dayan, Josh Tenenbaum, Angela Yu, & others
Neural representations of probability distributions

Jeffrey Beck (University of Rochester)
Bayesian Inference, Action Selection, and Learning with Probabilistic Population Codes
Presentation (PDF File)
15:00-16:00
Stuart Russell (University of California, Berkeley (UC Berkeley))
Hierarchical reinforcement learning
16:00-16:30
Break
16:30-17:30
Josh Tenenbaum (Massachusetts Institute of Technology)
Models of human action understanding and social cognition as inverse decision-making

Monday, July 23, 2007

Morning Session

08:00-09:00
Check-in & Continental Breakfast
09:00-10:00
Laurence Maloney (New York University)
Statistical decision theory as a framework for cognition and action.
10:00-10:15
Break
10:15-11:15
Nathaniel Daw (New York University)
Neuro- and behavioral economic analysis of human choice and learning
11:15-11:30
Break
11:30-12:30
Konrad Koerding (Northwestern University Medical School)
Using Decision Theory to understand Motor Control

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45-14:45
Breakout Session

Craig Fox (UCLA)
Prospect theory and support theory
Reading: "Belief and Preference in Decision Under Uncertainty", by Craig R. Fox & Kelly E. See
Presentation (PDF File)
15:00-16:00
Josh Tenenbaum (Massachusetts Institute of Technology)
Rational analysis of human memory and prediction
16:00-16:30
Break
16:30-17:30
Rich Shiffrin (Indiana University)
Bayesian models of memory retrieval

Tuesday, July 24, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:00
Amy Perfors (Massachusetts Institute of Technology)
Grammar induction in language
10:00-10:15
Break
10:15-11:15
Alan Yuille (University of California, Los Angeles (UCLA))
Grammer induction in vision
11:15-11:30
Break
11:30-12:15
Josh Tenenbaum (Massachusetts Institute of Technology)
Cognitive development as a computational challenge: the grammar analogy

Afternoon Session

12:15-13:15
Lunch (on your own)
13:30-14:30
Breakout Session

Opportunities for mathematicians and statisticians in cognitive science and neuroscience, with Alan Yuille, Mark Green, Yingnian Wu, Noah Goodman, others

Faculty Center
14:45-15:30
Charles Kemp (Massachusetts Institute of Technology)
The development of structured representations
15:30-15:50
Break
15:50-16:25
Tom Griffiths (University of California, Berkeley (UC Berkeley))
Development of Causal Theories
16:25-16:45
Break
16:45-17:30
Noah Goodman (Massachusetts Institute of Technology)
Learning to be causal
19:30
Discussion and Q & A on grammar induction and unsupervised learning for structured statistical models with Alan Yuille, Josh Tenenbaum, Noah Goodman and Tom Griffiths

Math Sci 4000A

Wednesday, July 25, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:00
Konrad Koerding (Northwestern University Medical School)
Causal Inference in Motor Learning and Adaptation
10:00-10:15
Break
10:15-11:15
Ladan Shams (UCLA)
Multisensory integration-segregation as Bayesian inference
11:15-11:30
Break
11:30-12:30
Jerome Busemeyer (Indiana University)
Challenges for Bayes

Afternoon Session

12:30-13:30
Lunch (on your own)
13:45
Symposium (Future Challenges): Josh Tenenbaum, Tom Griffiths, Alan Yuille, Keith Holyoak, Rich Shiffrin

Thursday, July 26, 2007

Morning Session

08:00-09:00
Continental Breakfast
09:00-10:00
Student Research Symposium
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