Yan Karklin
Affiliations: | New York University, New York, NY, United States |
Area:
Computation & TheoryWebsite:
http://www.cns.nyu.edu/~yan/Google:
"Yan Karklin"Mean distance: 13.55 (cluster 17) | S | N | B | C | P |
Parents
Sign in to add mentor| Michael S. Lewicki | grad student | 2007 | Carnegie Mellon | |
| (Hierarchical statistical models of computation in the visual cortex.) | ||||
| Eero P. Simoncelli | post-doc | 2008-2013 | NYU | |
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Publications
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| Karklin Y, Ekanadham C, Simoncelli EP. (2012) Hierarchical spike coding of sound. Advances in Neural Information Processing Systems. 2012: 3032-3040 |
| Karklin Y, Simoncelli EP. (2011) Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons. Advances in Neural Information Processing Systems. 24: 999-1007 |
| Karklin Y, Simoncelli EP. (2011) Efficient coding of natural images with a population of noisy Linear-Nonlinear neurons Advances in Neural Information Processing Systems 24: 25th Annual Conference On Neural Information Processing Systems 2011, Nips 2011 |
| Karklin Y, Lewicki MS. (2009) Emergence of complex cell properties by learning to generalize in natural scenes. Nature. 457: 83-6 |
| Karklin Y, Lewicki MS. (2005) A hierarchical Bayesian model for learning nonlinear statistical regularities in nonstationary natural signals. Neural Computation. 17: 397-423 |
| Karklin Y, Lewicki MS. (2005) Is early vision optimized for extracting higher-order dependencies? Advances in Neural Information Processing Systems. 635-642 |
| Karklin Y, Lewicki MS. (2003) Learning higher-order structures in natural images. Network (Bristol, England). 14: 483-99 |
| Karklin Y, Lewicki MS. (2003) A model for learning variance components of natural images Advances in Neural Information Processing Systems |