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Week |
Topics |
Slides |
Papers |
Presenter |
Week 1
(9/4, 9/6) |
- From machine learning to brain-like cognitive learning
- Brain as a physical, thermodynamic computer
- Perception-action cycles and Carnot cycles
- Models of action-perception-learning cycles
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Action-Perception Learning Cycles
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Week 2
(9/11, 9/13) |
- Gordon, G., Kaplan, D. M., Lankow, B., Little, D. Y.-J., Sherwin, J., Suter, B. A., and Thaler, L., Toward an integrated approach to perception and action: conference report and future directions, Frontiers in Systems Neuroscience, 5(20):1-6, 2011.
- Fuster, J. M., The prefrontal cortex - an update: Time is of the essence, Neuron, 30:319-333, 2001.
(Ref : Fuster, J. M., The cognit: A network model of cortical representation, International Journal of Psychophysiology, 60:125-132, 2006.)
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2-1
2-2
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2-1
2-2-1
2-2-2
|
Beom-Jin Lee
Hyo-Sun Chun
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Week 3
(9/18, 9/20) |
- Pickering, M. and Garrod, S., An integrated theory of language production and comprehension, Behavioral and Brain Sciences, 2012. (in press)
- Clark, A., Whatever next? Predictive brains, situated agents, and the future of cognitive science, Behavioral and Brain Sciences, 2012. (in press)
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3-1
3-2
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3-1
3-2
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Sang-woo Lee
Eun-seok Lee
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Week 4
(9/25, 9/27) |
- Fry, R. L., Neural statics and dynamics, Neurocomputing, 65-66:455-462, 2005.
(Ref : Fry, R. L., Computation by neural and cortical systems, BMC Neuroscience, 9(Suppl 1):P66, 2008.)
- Reviews and discussion (9/27)
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4-1
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4-1-1
4-1-2
|
Sungjoo Ha, MyoungHoon Ha
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Week 5
(10/2, 10/4) |
- Friston, K., The free-energy principle: a rough guide to the brain?, Trends in Cognitive Sciences, 2009.
- Dayan, P. & Daw, N. D., Connections between computational and neurobiological perspectives on decision making, Cognitive, Affective, & Behavioral Neuroscience, 8(4):429-453, 2008.
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5-1
5-2
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5-1
5-2
|
Poudel Gokrna
Daeseob Lim |
Week 6
(10/9, 10/11) |
- Zahedi, K., Ay,N., and Der, R., Higher coordination with less control-A result of information maximization in the sensorimotor loop, Adaptive Behavior, 18(3-4):338-355, 2010.
- Tishby, N. & Polani, D., Information theory of decisions and actions, In: Perception-Reason-Action Cycle: Models, Algorithms and Systems, 2010.
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6-1
6-2
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6-1
6-2
|
Sangam Uprety
Jongki Cho, Shinchoo Kim |
Week 7
(10/16, 10/18) |
- Reviews and discussion (10/16)
- Exam 1 (10/18)
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Week 8
(10/23, 10/25) |
- Bayesian inference and estimation
- Barber, D., Cemgil, A, T. and Chiappa, S., Inference and estimation in probabilistic time series models [1]
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8-1
8-2
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Week 9
(10/30, 11/1) |
- Barber, D., Cemgil, A, T. and Chiappa, S., Inference and estimation in probabilistic time series models [1]
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Week 10
(11/6, 11/8) |
- Haykin, S., Kalman filters [2]
- Extensions and variations
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10-1
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Week 11
(11/13, 11/15) |
- Pouget, A. Dayan, P., & Zemel, R. S., Inference and computation with population codes, Annual Review of Neuroscience, 26:381-410, 2003.
- Knill, D. C. & Pouget, A., The Bayesian brain: the role of uncertainty in neural coding and computation, Trends in Neurosciences, 27(12):712-719, 2004.
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11-1
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11-1
11-2
|
Jisu Kim, Hahn SangWook
Chung-Yeon Lee, Zhiqiang Ma |
Week 12
(11/20, 11/22) |
- A tutorial on particle filters [3]
- Bayesian evolutionary algorithms
|
Kalman Filter
Particle Filter
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12-1
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Week 13
(11/27, 11/29) |
- Reviews and discussion (11/27)
- Exam 2 (11/29)
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Week 14
(12/4, 12/6) |
- Osborne, L. C., Palmer, S. E., Lisberger, S. G., and Bialek, W., The neural basis for combinatorial coding in a cortical population response, Journal of Neuroscience, 28,13522-13531, 2008.
- Bach, D. and Dolan, R. J., Knowing how much you don't know: a neural organization of uncertainty estimates, Nature Reviews Neuroscience, 13:572-586, 2012.
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14-1
14-2
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Roger Paris
Jonathan Boellke |
Week 15
(12/11, 12/13) |
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12/13
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Place: 302-308 |
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