Browse > Article

Cognitive Computing III: Deep Dynamic Prediction - 실시간 예측결정 추론  

Zhang, Byoung-Tak (서울대학교)
Kim, Hyun-Soo (한국연구재단)
Publication Information
Communications of the Korean Institute of Information Scientists and Engineers / v.30, no.1, 2012 , pp. 101-111 More about this Journal
Keywords
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Hopfield, J. J, Neural networks and physical systems with emergent collective computational abilities, Proceedings of the National Academy of Sciences of the USA, 79(8):2554-2558,1982.   DOI
2 Rumelhart, D. & McClelland, J., Parallel Distributed Processing: Explorations in the Microstructure of Cognition, MIT Press, 1986.
3 Bishop, C., Neural Networks for Pattern Recognition, Oxford University Press, 1995.
4 Mackay, D. J. C., Information Theory, Inference, and Learning Algorithms, Cambridge University Press, 2003.
5 Koller, D., Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009.
6 Ma, W. J., Beck, J. M., Latham, P. E., & Pouget, A., Bayesian inference with probabilistic population codes, Nature Neuroscience, 9: 1432-1438, 2006.   DOI
7 Pouget, A., Dayan, P., & Zemel, R. S., Inference and computation with population codes, Annual Review of Neuroscience, 26:381-410, 2003.   DOI
8 Port, R.F. & van Gelder, T., Mind as Motion: Explorations in the Dynamics of Cognition, MIT Press, 1995.
9 Kelso,J. A. S., Dynamic Patterns: the Self-organization of Brain and Behavior, MIT Press, 1995.
10 Spivey, M., The Continuity of Mind, Oxford University Press, 2007.
11 Knill, D. & Richards, W (Eds.), Perception as Bayesian Inference, Cambridge University Press, 1996.
12 Rao, R., Olshausen, B. A., Lewicki, M. S. (Eds.), Probabilistic Models of the Brain: Perception and Neural Function, MIT Press, 2002.
13 Knill, D. & Pouget, A., The Bayesian brain: the role of uncertainty in neural coding and computation, Trends in Neurosciences, 27(12):712-719, 2004.   DOI
14 Doya, K., Ishii, S., Pouget, A., & Rao, R. (Eds.), Bayesian Brain: Probabilistic Approaches to Neural Coding, MIT Press, 2007.
15 Ernst, M.O. & Banks, M.S., Humans integrate visual and haptic information in a statistically optimal fashion, Nature, 415:429-433, 2002.   DOI
16 Kording, K. P. & Wolpert, D. M., Bayesian integration in sensorimotor learning, Nature, 427:244-247, 2004.   DOI
17 Bar, M. (Eds.), Predictions in the Brain: Using Our Past to Generate a Future, Oxford University Press, 2011 .
18 Von der Malsburg, C., Phillips, W. A., and Singer, W. (Eds.), Dynamic Coordination in the Brain: From Neurons to Mind, MIT Press, 2010.
19 Hebb, D., The Organization of Behavior-A Neuropsychological Theory, Wiley, 1949.
20 Lashley, K. S., Brain Mechanisms and Intelligence (2nd Ed.), Dover Publications, 1963 .
21 장병탁, 여무송, Cognitive Computing I: Multisensory Perceptual Intelligence-실세계 지각행동 지능, 정보과학회지, 30(1):75-87, 2012.
22 Sendhoff, B., Korner, E., Spoms, O., Ritter, H., & Doya, K. (Eds.), Creating Brain-Like Intelligence: From Basic Principles to Complex Intelligent Systems, Springer-Verlag, 2009.
23 Modha, D. S., Ananthanarayanan, R., Esser, S. K., Ndirango, A., Sherbondy, A.J., & Singh, R, Cognitive computing, Communications of the ACM, 54(8):62-71, 2011.
24 Marr, D., Vision, Freeman and Company, 1982.
25 장병탁, 이동훈, Cognitive Computing II: Machine Vision-Language Learning-실생활 시각언어 학습, 정보과학회지, 30(1):88-100, 2012.
26 Rogers, T. & McClelland, J., Semantic cognition: a parallel distributed processing approach, MIT Press, 2006.
27 Hnton, G. & Anderson, J. A., Parallel Models of Associative Memory, Erlbaum, 1981.
28 Feldman, J. A. & Ballard, D. H., Connectionist models and their properties, Cognitive Science, 6:205-254, 1982.   DOI
29 Trommershaeuser, J., Koerding, K., and Landy, M. S. (Eds.), Sensory Cue Integration, Oxford University Press, 2011.
30 Chater, N. & Oaksford, M. (Eds.), The Probabilistic Mind: Prospects for Bayesian Cognitive Science, Oxford University Press, 2008.
31 Griffiths, T., Charles Kemp, C. &Tenenbaum, J., Bayesian models of cognition, Sun, R (Ed.) Cambridge Handbook of Computational Psychology, 2008.
32 Oaksford, M. & Chater, N., Cognition and Conditionals: Probability and Logic in Human Thinking, Oxford Univ. Press, 2010.
33 DiVincenzo, D. P., Quantum computation, Science, 270 (5234):255-261, 1995.   DOI
34 Lee, J.-H., Lee, S. H., Chung, W.-H., Lee, E. S., Park, T. H., Deaton, R., & Zhang, B.-T., A DNA assembly model of sentence generation, BioSystems, 106:51-56, 2011.   DOI
35 Bennett, C., The thermodynamics of computation-a review, International Journal of Theoretical Physics, 1982.
36 Hinton, G. & Salakhutdinov, R., Reducing the dimensionality of data with neural networks, Science, 313 (5786):504-507,2006.   DOI
37 Adleman, L., Molecular computation of solutions to combinatorial problems, Science, 266(5187): 1021-1024, 1994.   DOI
38 Lim, H.-W., Lee, S.H., Yang, K.-A., Lee, J.Y., Yoo, S.-I., Park, T.H. & Zhang, B.-T., In vitro molecular pattern classification via DNA-based weighted sum operation, BioSystems, 100(1):1-7,2010.   DOI
39 Zhang, B.-T., Self-development learning: constructing optimal size neural networks via incremental data selection, Arbeitspapiere der German National Research Center for Computer Science (GMD), No. 768, 1993.
40 LeCun, Y. & Bengio, Y., Convolutional Networks for Images Speech and Time Series, The Handbook of Brain Theory and Neural Networks, MIT Press, 1995.
41 Hawkins, J. & Blakeslee, S., On Intelligence, Times Books, 2005.
42 Friston, K., Hierarchical models in the brain, PLoS Computational Biololgy, 4(11): e1000211, 2008.   DOI
43 Nilsson, N. J., Eye on the prize, AI Magazine, 16(2): 9-17,1995.