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Items: 9

1.

Human-level concept learning through probabilistic program induction.

Lake BM, Salakhutdinov R, Tenenbaum JB.

Science. 2015 Dec 11;350(6266):1332-8. doi: 10.1126/science.aab3050.

2.

Deep learning for neuroimaging: a validation study.

Plis SM, Hjelm DR, Salakhutdinov R, Allen EA, Bockholt HJ, Long JD, Johnson HJ, Paulsen JS, Turner JA, Calhoun VD.

Front Neurosci. 2014 Aug 20;8:229. doi: 10.3389/fnins.2014.00229. eCollection 2014.

3.

Restricted Boltzmann machines for neuroimaging: an application in identifying intrinsic networks.

Hjelm RD, Calhoun VD, Salakhutdinov R, Allen EA, Adali T, Plis SM.

Neuroimage. 2014 Aug 1;96:245-60. doi: 10.1016/j.neuroimage.2014.03.048. Epub 2014 Mar 28.

4.

Guest editors' introduction: special section on learning deep architectures.

Bengio S, Deng L, Larochelle H, Lee H, Salakhutdinov R.

IEEE Trans Pattern Anal Mach Intell. 2013 Aug;35(8):1795-7. No abstract available.

PMID:
23946944
5.

Learning with hierarchical-deep models.

Salakhutdinov R, Tenenbaum JB, Torralba A.

IEEE Trans Pattern Anal Mach Intell. 2013 Aug;35(8):1958-71. doi: 10.1109/TPAMI.2012.269.

PMID:
23787346
6.

An efficient learning procedure for deep Boltzmann machines.

Salakhutdinov R, Hinton G.

Neural Comput. 2012 Aug;24(8):1967-2006. doi: 10.1162/NECO_a_00311. Epub 2012 Apr 17.

PMID:
22509963
7.

Discovering binary codes for documents by learning deep generative models.

Hinton G, Salakhutdinov R.

Top Cogn Sci. 2011 Jan;3(1):74-91. doi: 10.1111/j.1756-8765.2010.01109.x. Epub 2010 Aug 18.

8.

Reducing the dimensionality of data with neural networks.

Hinton GE, Salakhutdinov RR.

Science. 2006 Jul 28;313(5786):504-7.

9.

Spontaneous quantal and non-quantal release of acetylcholine at mouse endplate during onset of hypoxia.

Bukharaeva EA, Salakhutdinov RI, Vyskocil F, Nikolsky EE.

Physiol Res. 2005;54(2):251-5.

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