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y¶@”N@ŒŽz 1977 ”N 5 ŒŽ
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2001 ”N 3 ŒŽ   –kŠC“¹‘åŠwHŠw•”î•ñHŠw‰È‘²‹Æ
2003 ”N 3 ŒŽ   –kŠC“¹‘åŠw‘åŠw‰@HŠwŒ¤‹†‰ÈƒVƒXƒeƒ€î•ñHŠwêUCŽm‰Û’öC—¹
2006 ”N 3 ŒŽ   ‹ž“s‘åŠw‘åŠw‰@—ŠwŒ¤‹†‰È•¨—ŠwE‰F’ˆ•¨—ŠwêU”ŽŽm‰Û’öC—¹
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2006 ”N 5 ŒŽ   •Ä‘ƒJ[ƒlƒM[ƒƒƒ“‘åŠw“ŒvŠw‰Èƒ|ƒXƒhƒNŒ¤‹†ˆõ
2010 ”N 5 ŒŽ   “Œv”—Œ¤‹†Š”—E„˜_Œ¤‹†Œn•‹³
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y˜_@@@•¶z (7) S. Koyama, L. C. Perez-Bolde, C. R. Shalizi and R. E. Kass (2010), Approximate methods for state-space models, Journal of the American Statistical Association, 105, 170-180.
(6) S. Koyama, U. T. Eden, E. N. Brown and R. E. Kass (2010), Bayesian decoding of neural spike trains, Annals of the Institute of Statistical Mathematics, 62, 37-59.
(5) S. Koyama and R. E. Kass (2008), Spike train probability models for stimulus-driven leaky integrate-and-fire neurons, Neural Computation, 20, 1776-1795.
(4) S. Koyama, K. Shimokawa and S. Shinomoto (2007), Phase transitions in the estimation of event-rate: a path integral analysis, Journal of Physics A: Mathematical and General, 40, E383-E390.
(3) S. Koyama and S. Shinomoto (2005), Empirical Bayes interpretations of random point events, Journal of Physics A: Mathematical and General, 38, L531-L537.
(2) S. Koyama and S. Shinomoto (2004), Histogram bin width selection for time-dependent Poisson processes, Journal of Physics A: Mathematical and General, 37, 7255-7265.
(1) S. Koyama (2001), Storage capacity of two-dimensional neural networks, Physical Review E, 65, 016124.
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