Showing results (11-20 of 139) with videos related to
Sort By:
Pageof 14
Journal of Computational Neuroscience|April 29, 2009
Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-space modelsShinsuke Koyama, Liam PaninskiNetwork (Bristol, England)|June 8, 2013
Computing loss of efficiency in optimal Bayesian decoders given noisy or incomplete spike trainsCarl Smith, Liam PaninskiIEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|February 13, 2009
Bayesian image recovery for dendritic structures under low signal-to-noise conditionsGeoffrey Fudenberg, Liam PaninskiNeural Computation|September 24, 2014
On quadrature methods for refractory point process likelihoodsGonzalo Mena, Liam PaninskiJournal of Neuroscience Methods|December 25, 2010
Kalman filter mixture model for spike sorting of non-stationary dataAna Calabrese, Liam PaninskiJournal of Computational Neuroscience|March 23, 2012
A Bayesian compressed-sensing approach for reconstructing neural connectivity from subsampled anatomical dataYuriy Mishchenko, Liam PaninskiNetwork (Bristol, England)|October 19, 2007
Common-input models for multiple neural spike-train dataJayant E Kulkarni, Liam PaninskiJournal of Computational Neuroscience|July 9, 2013
Fast inference in generalized linear models via expected log-likelihoodsAlexandro D Ramirez, Liam PaninskiJournal of Computational Neuroscience|August 24, 2011
Optimal experimental design for sampling voltage on dendritic trees in the low-SNR regimeJonathan Hunter Huggins, Liam PaninskiProgress in Brain Research|October 11, 2007
Statistical models for neural encoding, decoding, and optimal stimulus designLiam Paninski, Jonathan Pillow, Jeremy LewiPageof 14