Liam Paninski

2009
22	EE	Geoff Fudenberg, Liam Paninski: Bayesian Image Recovery for Dendritic Structures Under Low Signal-to-Noise Conditions. IEEE Transactions on Image Processing 18(3): 471-482 (2009)
2008
21	EE	Jeremy Lewi, Robert J. Butera, David M. Schneider, Sarah M. N. Woolley, Liam Paninski: Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds. NIPS 2008: 945-952
20	EE	Liam Paninski: A Coincidence-Based Test for Uniformity Given Very Sparsely Sampled Discrete Data. IEEE Transactions on Information Theory 54(10): 4750-4755 (2008)
19	EE	Liam Paninski, Masanao Yajima: Undersmoothed Kernel Entropy Estimators. IEEE Transactions on Information Theory 54(9): 4384-4388 (2008)
18	EE	Liam Paninski, Adrian Haith, Gabor Szirtes: Integral equation methods for computing likelihoods and their derivatives in the stochastic integrate-and-fire model. Journal of Computational Neuroscience 24(1): 69-79 (2008)
2006
17	EE	Jeremy Lewi, Robert J. Butera, Liam Paninski: Real-time adaptive information-theoretic optimization of neurophysiology experiments. NIPS 2006: 857-864
16	EE	Liam Paninski: The most likely voltage path and large deviations approximations for integrate-and-fire neurons. Journal of Computational Neuroscience 21(1): 71-87 (2006)
15	EE	Liam Paninski: The Spike-Triggered Average of the Integrate-and-Fire Cell Driven by Gaussian White Noise. Neural Computation 18(11): 2592-2616 (2006)
2005
14	EE	Misha Ahrens, Quentin Huys, Liam Paninski: Large-scale biophysical parameter estimation in single neurons via constrained linear regression. NIPS 2005
13	EE	Liam Paninski: Nonparametric inference of prior probabilities from Bayes-optimal behavior. NIPS 2005
12	EE	Liam Paninski: Asymptotic Theory of Information-Theoretic Experimental Design. Neural Computation 17(7): 1480-1507 (2005)
11	EE	Liam Paninski, Jonathan Pillow, Eero P. Simoncelli: Comparing integrate-and-fire models estimated using intracellular and extracellular data. Neurocomputing 65-66: 379-385 (2005)
2004
10	EE	Liam Paninski: Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning. NIPS 2004
9	EE	Liam Paninski: Variational Minimax Estimation of Discrete Distributions under KL Loss. NIPS 2004
8		Liam Paninski: Estimating Entropy on m Bins Given Fewer than m Samples. IEEE Transactions on Information Theory 50(9): 2200-2203 (2004)
7	EE	Liam Paninski, Jonathan Pillow, Eero P. Simoncelli: Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model. Neural Computation 16(12): 2533-2561 (2004)
2003
6	EE	Liam Paninski: Design of Experiments via Information Theory. NIPS 2003
5	EE	Jonathan Pillow, Liam Paninski, Eero P. Simoncelli: Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model. NIPS 2003
4	EE	Mijail Serruya, Nicholas G. Hatsopoulos, Matthew Fellows, Liam Paninski, John Donoghue: Robustness of neuroprosthetic decoding algorithms. Biological Cybernetics 88(3): 219-228 (2003)
3	EE	Liam Paninski: Estimation of Entropy and Mutual Information. Neural Computation 15(6): 1191-1253 (2003)
2002
2	EE	Liam Paninski: Convergence Properties of Some Spike-Triggered Analysis Techniques. NIPS 2002: 173-180
2001
1	EE	Liam Paninski, Michael J. Hawken: Stochastic optimal control and the human oculomotor system. Neurocomputing 38-40: 1511-1517 (2001)

Coauthor Index

1	Misha Ahrens	[14]
2	Robert J. Butera	[17] [21]
3	John Donoghue	[4]
4	Matthew Fellows	[4]
5	Geoff Fudenberg	[22]
6	Adrian Haith	[18]
7	Nicholas G. Hatsopoulos	[4]
8	Michael J. Hawken	[1]
9	Quentin Huys	[14]
10	Jeremy Lewi	[17] [21]
11	Jonathan Pillow	[5] [7] [11]
12	David M. Schneider	[21]
13	Mijail Serruya	[4]
14	Eero P. Simoncelli	[5] [7] [11]
15	Gabor Szirtes	[18]
16	Sarah M. N. Woolley	[21]
17	Masanao Yajima	[19]

Colors in the list of coauthors