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Journal 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 LewiConference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference|October 20, 2007
Efficient model-based design of neurophysiological experimentsJeremy Lewi, Robert Butera, Liam PaninskiNeural Computation|October 22, 2008
Sequential optimal design of neurophysiology experimentsJeremy Lewi, Robert Butera, Liam PaninskiPlos Computational Biology|May 9, 2009
Smoothing of, and parameter estimation from, noisy biophysical recordingsQuentin J M Huys, Liam PaninskiPlos Computational Biology|March 15, 2017
Fast online deconvolution of calcium imaging dataJohannes Friedrich, Pengcheng Zhou, Liam PaninskiJournal of Computational Neuroscience|May 12, 2007
Integral equation methods for computing likelihoods and their derivatives in the stochastic integrate-and-fire modelLiam Paninski, Adrian Haith, Gabor SzirtesJournal of the Optical Society of America. A, Optics, Image Science, and Vision|November 4, 2009
The relationship between optimal and biologically plausible decoding of stimulus velocity in the retinaEdmund C Lalor, Yashar Ahmadian, Liam PaninskiNeural Computation|October 23, 2010
Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trainsJonathan W Pillow, Yashar Ahmadian, Liam PaninskiPageof 15