Stuart Geman

Affiliations: 
Brown University, Providence, RI 
Area:
Mathematics
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"Stuart Geman"

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Shih-Hsiu Huang grad student 2001 Brown
Brian O. Lucena grad student 2002 Brown
Asohan Amarasingham grad student 2004 Brown
Ting-Li Chen grad student 2005 Brown
Matthew T. Harrison grad student 2005 Brown
Ya Jin grad student 2006 Brown
Lo-Bin Chang grad student 2010 Brown
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Publications

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Amarasingham A, Geman S, Harrison MT. (2015) Ambiguity and nonidentifiability in the statistical analysis of neural codes. Proceedings of the National Academy of Sciences of the United States of America. 112: 6455-60
Geman D, Geman S, Hallonquist N, et al. (2015) Visual Turing test for computer vision systems. Proceedings of the National Academy of Sciences of the United States of America. 112: 3618-23
Zhou G, Geman S, Buhmann JM. (2014) Sparse feature selection by information theory Ieee International Symposium On Information Theory - Proceedings. 926-930
Chen TL, Geman S. (2014) Image warping using radial basis functions Journal of Applied Statistics. 41: 242-258
Chang LB, Geman S, Hsieh F, et al. (2013) Invariance in the recurrence of large returns and the validation of models of price dynamics. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 88: 022116
Chang LB, Geman S. (2013) Empirical scaling laws and the aggregation of non-stationary data Physica a: Statistical Mechanics and Its Applications. 392: 5046-5052
Amarasingham A, Harrison MT, Hatsopoulos NG, et al. (2012) Conditional modeling and the jitter method of spike resampling. Journal of Neurophysiology. 107: 517-31
Chang LB, Jin Y, Zhang W, et al. (2011) Context, computation, and optimal ROC performance in hierarchical models International Journal of Computer Vision. 93: 117-140
Harrison MT, Geman S. (2009) A rate and history-preserving resampling algorithm for neural spike trains. Neural Computation. 21: 1244-58
Chen TL, Geman S. (2008) On the minimum entropy of a mixture of unimodal and symmetric distributions Ieee Transactions On Information Theory. 54: 3166-3174
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