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Robert Haslinger

Showing results (1-10 of 11) with videos related to

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Neural Computation|July 9, 2010
Discrete time rescaling theorem: determining goodness of fit for discrete time statistical models of neural spikingRobert Haslinger, Gordon Pipa, Emery Brown
Neural Computation|March 15, 2011
Applying the multivariate time-rescaling theorem to neural population modelsFelipe Gerhard, Robert Haslinger, Gordon Pipa
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|September 26, 2012
Statistical modeling approach for detecting generalized synchronizationJohannes Schumacher, Robert Haslinger, Gordon Pipa
Neural Computation|September 22, 2009
The computational structure of spike trainsRobert Haslinger, Kristina Lisa Klinkner, Cosma Rohilla Shalizi
Physical Review Letters|September 28, 2004
Quantifying self-organization with optimal predictorsCosma Rohilla Shalizi, Kristina Lisa Shalizi, Robert Haslinger
Frontiers in Computational Neuroscience|July 31, 2013
Missing mass approximations for the partition function of stimulus driven Ising modelsRobert Haslinger, Demba Ba, Ralf Galuske, et al.
Physical Review Letters|March 14, 2003
First-order superconducting transition near a ferromagnetic quantum critical pointAndrey V Chubukov, Alexander M Finkel'stein, Robert Haslinger, et al.
Plos One|July 18, 2012
Context matters: the illusive simplicity of macaque V1 receptive fieldsRobert Haslinger, Gordon Pipa, Bruss Lima, et al.
Neural Computation|April 24, 2013
Encoding through patterns: regression tree-based neuronal population modelsRobert Haslinger, Gordon Pipa, Laura D Lewis, et al.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|April 12, 2006
Automatic filters for the detection of coherent structure in spatiotemporal systemsCosma Rohilla Shalizi, Robert Haslinger, Jean-Baptiste Rouquier, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Neural Computation|July 9, 2010
Discrete time rescaling theorem: determining goodness of fit for discrete time statistical models of neural spikingRobert Haslinger, Gordon Pipa, Emery Brown
Neural Computation|March 15, 2011
Applying the multivariate time-rescaling theorem to neural population modelsFelipe Gerhard, Robert Haslinger, Gordon Pipa
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|September 26, 2012
Statistical modeling approach for detecting generalized synchronizationJohannes Schumacher, Robert Haslinger, Gordon Pipa
Neural Computation|September 22, 2009
The computational structure of spike trainsRobert Haslinger, Kristina Lisa Klinkner, Cosma Rohilla Shalizi
Physical Review Letters|September 28, 2004
Quantifying self-organization with optimal predictorsCosma Rohilla Shalizi, Kristina Lisa Shalizi, Robert Haslinger
Frontiers in Computational Neuroscience|July 31, 2013
Missing mass approximations for the partition function of stimulus driven Ising modelsRobert Haslinger, Demba Ba, Ralf Galuske, et al.
Physical Review Letters|March 14, 2003
First-order superconducting transition near a ferromagnetic quantum critical pointAndrey V Chubukov, Alexander M Finkel'stein, Robert Haslinger, et al.
Plos One|July 18, 2012
Context matters: the illusive simplicity of macaque V1 receptive fieldsRobert Haslinger, Gordon Pipa, Bruss Lima, et al.
Neural Computation|April 24, 2013
Encoding through patterns: regression tree-based neuronal population modelsRobert Haslinger, Gordon Pipa, Laura D Lewis, et al.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|April 12, 2006
Automatic filters for the detection of coherent structure in spatiotemporal systemsCosma Rohilla Shalizi, Robert Haslinger, Jean-Baptiste Rouquier, et al.
Pageof 2