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Volumn , Issue , 2013, Pages

Universal models for binary spike patterns using centered Dirichlet processes

Author keywords

[No Author keywords available]

Indexed keywords

GEODESY;

EID: 84898959554     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (12)

References (18)
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  • 2
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    • High-dimensional Ising model selection using L1- regularized logistic regression
    • P. Ravikumar, M. Wainwright, and J. Lafferty. High-dimensional Ising model selection using L1- regularized logistic regression. The Annals of Statistics, 38(3):1287-1319, 2010.
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    • Ravikumar, P.1    Wainwright, M.2    Lafferty, J.3
  • 3
    • 79959354385 scopus 로고    scopus 로고
    • Sparse low-order interaction network underlies a highly correlated and learnable neural population code
    • E. Ganmor, R. Segev, and E. Schneidman. Sparse low-order interaction network underlies a highly correlated and learnable neural population code. Proceedings of the National Academy of Sciences, 108(23):9679-9684, 2011.
    • (2011) Proceedings of the National Academy of Sciences , vol.108 , Issue.23 , pp. 9679-9684
    • Ganmor, E.1    Segev, R.2    Schneidman, E.3
  • 4
    • 33646170322 scopus 로고    scopus 로고
    • Weak pairwise correlations imply strongly correlated network states in a neural population
    • Apr
    • E. Schneidman, M. J. Berry, R. Segev, and W. Bialek. Weak pairwise correlations imply strongly correlated network states in a neural population. Nature, 440(7087):1007-1012, Apr 2006.
    • (2006) Nature , vol.440 , Issue.7087 , pp. 1007-1012
    • Schneidman, E.1    Berry, M.J.2    Segev, R.3    Bialek, W.4
  • 7
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    • Reducing the dimensionality of data with neural networks
    • G. E. Hinton and R. R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, 2006.
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    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 9
    • 85162002902 scopus 로고    scopus 로고
    • Near-maximum entropy models for binary neural representations of natural images
    • M. Bethge and P. Berens. Near-maximum entropy models for binary neural representations of natural images. Advances in neural information processing systems, 20:97-104, 2008.
    • (2008) Advances in Neural Information Processing Systems , vol.20 , pp. 97-104
    • Bethge, M.1    Berens, P.2
  • 10
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    • Nonparametric bayesian data analysis
    • P. Müller and F. A. Quintana. Nonparametric bayesian data analysis. Statistical science, 19(1):95-110, 2004.
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    • Nonparametric modeling of neural point processes via stochastic gradient boosting regression
    • W. Truccolo and J. P. Donoghue. Nonparametric modeling of neural point processes via stochastic gradient boosting regression. Neural computation, 19(3):672-705, 2007.
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  • 18


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.