cached image

Yan Karklin

Affiliations: 
New York University, New York, NY, United States 
Area:
Computation & Theory
Website:
http://www.cns.nyu.edu/~yan/
Google:
"Yan Karklin"
Mean distance: 13.55 (cluster 17)
 
SNBCP

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
BETA: Related publications

Publications

You can help our author matching system! If you notice any publications incorrectly attributed to this author, please sign in and mark matches as correct or incorrect.

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, Meraz RF, Holbrook SR. (2005) Classification of non-coding RNA using graph representations of secondary structure. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 4-15
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
See more...