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

July 9 - 26, 2007

Schedule


Monday, July 9, 2007

9:00 - 10:00
Josh Tenenbaum (Massachusetts Institute of Technology)

Introduction to Probabilistic Models of Cognition

10:15 - 11:15
Josh Tenenbaum (Massachusetts Institute of Technology)

Basic Bayes: model fitting, model selection, and model averaging

11:30 - 12:30
1:45 - 2:45
Tom Griffiths (University of California, Berkeley (UC Berkeley))

Introduction to Graphical Models

3:00 - 4:00
Robert Jacobs (University of Rochester)

Bayesian Decision Theory

4:30 - 5:30
Ying Nian Wu (UCLA)

Information Theory


Tuesday, July 10, 2007

9:00 - 10:00
Alan Yuille (University of California, Los Angeles (UCLA))

Graphical Models in Vision

10:15 - 11:15
Alan Yuille (University of California, Los Angeles (UCLA))

HMMs and inference in graphical models I

11:30 - 12:30
Robert Jacobs (University of Rochester)

Ideal Observers and Ideal Actors

1:45 - 2:45
3:00 - 4:00
Alan Yuille (University of California, Los Angeles (UCLA))

HMMs and inference in graphical models II

4:30 - 5:30
Robert Jacobs (University of Rochester)

Sensory Cue Combination


Wednesday, July 11, 2007

9:00 - 10:00
Zoubin Ghahramani (University of Cambridge)

Probabilistic generative models and unsupervised learning I

10:15 - 11:15
Zoubin Ghahramani (University of Cambridge)

Probabilistic generative models and unsupervised learning II

11:30 - 12:30
Zoubin Ghahramani (University of Cambridge)

Nonparametric Bayesian Models

3:00 - 4:00
Tom Griffiths (University of California, Berkeley (UC Berkeley))

Modern Monte Carlo methods I: Importance sampling and sequential Monte Carlo

4:30 - 5:30
Tom Griffiths (University of California, Berkeley (UC Berkeley))

Modern Monte Carlo methods II: Markov chain Monte Carlo


Thursday, July 12, 2007

9:00 - 10:30
Zoubin Ghahramani (University of Cambridge)

Bayesian supervised learning and semi-supervised learning

11:00 - 12:30
3:00 - 4:15
Josh Tenenbaum (Massachusetts Institute of Technology)

Hierarchical Bayesian models of human inductive learning

4:30 - 5:30

Friday, July 13, 2007

9:00 - 9:45
Ying Nian Wu (UCLA)

Causal Models

9:50 - 10:45
Tom Griffiths (University of California, Berkeley (UC Berkeley))

Graphical models and human causal learning

11:15 - 12:00
12:05 - 12:50
Patricia Cheng (University of California, Los Angeles (UCLA))

Causal Reasoning in Humans and Rats

2:00 - 3:00
Alison Gopnik (University of California, Berkeley (UC Berkeley))

Causal Learning in Children

3:15 - 4:00
Tom Griffiths (University of California, Berkeley (UC Berkeley))

Modeling causal learning in children

4:30 - 5:30
Keith Holyoak (University of California, Los Angeles (UCLA))

From Causal Models to Analogical Inference


Monday, July 16, 2007

9:00 - 10:00
Stuart Russell (University of California, Berkeley (UC Berkeley))

Probability for Worlds with Things in Them

10:15 - 11:15
Brian Milch (Massachusetts Institute of Technology)

Relational Probability Models

11:30 - 12:30
Brian Milch (Massachusetts Institute of Technology)

Unknown Objects and BLOG

3:00 - 4:00
Josh Tenenbaum (Massachusetts Institute of Technology)

First-order probabilistic models in human cognition

4:30 - 5:30
Charles Kemp (Massachusetts Institute of Technology)

Learning relational theories


Tuesday, July 17, 2007

9:00 - 10:00
10:15 - 11:15
Stuart Geman (Brown University)

Hierarchy and Reusability in Image Analysis II

11:30 - 12:30
Alan Yuille (University of California, Los Angeles (UCLA))

Image Parsing

3:00 - 4:00
Fei-Fei Li (Princeton University)

Discovering Meaning in the Visual World

4:30 - 5:30
Dan Kersten (University of Minnesota, Twin Cities)

Human Object Perception: Bottom-up and Top-down


Wednesday, July 18, 2007

9:00 - 10:00
Mark Johnson (Brown University)

An introduction to grammars and parsing for language 1

10:15 - 11:15
Mark Johnson (Brown University)

An introduction to grammars and parsing for language 2
Updated Presentation

11:30 - 12:30
Roger Levy (University of California, San Diego)

Probabilistic sentence processing 1

3:00 - 4:00
Roger Levy (University of California, San Diego)

Probabilistic sentence processing 2

4:30 - 5:30
Mark Steyvers (University of California, Irvine (UCI))

Semantic Representations with Probabilistic Topic Models


Thursday, July 19, 2007

9:00 - 10:00
Peter Dayan (University College London)

Models of conditioning

10:15 - 11:15
John Kruschke (Indiana University)

Locally Bayesian Learning

11:30 - 12:30
3:00 - 4:00
Stuart Russell (University of California, Berkeley (UC Berkeley))

Reinforcement Learning

4:30 - 5:30

Friday, July 20, 2007

9:00 - 10:00
10:15 - 11:15
Peter Dayan (University College London)

Neural representation of value, reward and expectation

11:30 - 12:30
3:00 - 4:00
Stuart Russell (University of California, Berkeley (UC Berkeley))

Hierarchical reinforcement learning

4:30 - 5:30

Monday, July 23, 2007

9:00 - 10:00
10:15 - 11:15
11:30 - 12:30
Konrad Koerding (Northwestern University Medical School)

Using Decision Theory to understand Motor Control

3:00 - 4:00
Josh Tenenbaum (Massachusetts Institute of Technology)

Rational analysis of human memory and prediction

4:30 - 5:30
Rich Shiffrin (Indiana University)

Bayesian models of memory retrieval


Tuesday, July 24, 2007

9:00 - 10:00
Amy Perfors (Massachusetts Institute of Technology)

Grammar induction in language

10:15 - 11:15
Alan Yuille (University of California, Los Angeles (UCLA))

Grammer induction in vision

11:30 - 12:15
Josh Tenenbaum (Massachusetts Institute of Technology)

Cognitive development as a computational challenge: the grammar analogy

2:45 - 3:30
Charles Kemp (Massachusetts Institute of Technology)

The development of structured representations

3:50 - 4:25
Tom Griffiths (University of California, Berkeley (UC Berkeley))

Development of Causal Theories

4:45 - 5:30
Noah Goodman (Massachusetts Institute of Technology)

Learning to be causal


Wednesday, July 25, 2007

9:00 - 10:00
Konrad Koerding (Northwestern University Medical School)

Causal Inference in Motor Learning and Adaptation

10:15 - 11:15
11:30 - 12:30
Jerome Busemeyer (Indiana University)

Challenges for Bayes