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Publications of Author

1. Misha Ahrens, Quentin Huys, Liam Paninski
   Large-scale biophysical parameter estimation in single neurons via constrained linear regression. [Citation Graph (0, 0)][DBLP]
   NIPS, 2005, pp:- [Conf]
   
2. Liam Paninski
   Convergence Properties of Some Spike-Triggered Analysis Techniques. [Citation Graph (0, 0)][DBLP]
   NIPS, 2002, pp:173-180 [Conf]
   
3. Liam Paninski
   Design of Experiments via Information Theory. [Citation Graph (0, 0)][DBLP]
   NIPS, 2003, pp:- [Conf]
   
4. Liam Paninski
   Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning. [Citation Graph (0, 0)][DBLP]
   NIPS, 2004, pp:- [Conf]
   
5. Liam Paninski
   Variational Minimax Estimation of Discrete Distributions under KL Loss. [Citation Graph (0, 0)][DBLP]
   NIPS, 2004, pp:- [Conf]
   
6. Liam Paninski
   Nonparametric inference of prior probabilities from Bayes-optimal behavior. [Citation Graph (0, 0)][DBLP]
   NIPS, 2005, pp:- [Conf]
   
7. Jonathan Pillow, Liam Paninski, Eero P. Simoncelli
   Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model. [Citation Graph (0, 0)][DBLP]
   NIPS, 2003, pp:- [Conf]
   
8. Mijail Serruya, Nicholas G. Hatsopoulos, Matthew Fellows, Liam Paninski, John Donoghue
   Robustness of neuroprosthetic decoding algorithms. [Citation Graph (0, 0)][DBLP]
   Biological Cybernetics, 2003, v:88, n:3, pp:219-228 [Journal]
   
9. Liam Paninski, Michael J. Hawken
   Stochastic optimal control and the human oculomotor system. [Citation Graph (0, 0)][DBLP]
   Neurocomputing, 2001, v:38, n:, pp:1511-1517 [Journal]
   
10. Liam Paninski, Jonathan Pillow, Eero P. Simoncelli
    Comparing integrate-and-fire models estimated using intracellular and extracellular data. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2005, v:65, n:, pp:379-385 [Journal]
    
11. Liam Paninski
    Estimation of Entropy and Mutual Information. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2003, v:15, n:6, pp:1191-1253 [Journal]
    
12. Liam Paninski
    Asymptotic Theory of Information-Theoretic Experimental Design. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2005, v:17, n:7, pp:1480-1507 [Journal]
    
13. Liam Paninski, Jonathan Pillow, Eero P. Simoncelli
    Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2004, v:16, n:12, pp:2533-2561 [Journal]
    
14. Liam Paninski
    The Spike-Triggered Average of the Integrate-and-Fire Cell Driven by Gaussian White Noise. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:11, pp:2592-2616 [Journal]
    
15. Liam Paninski
    Estimating Entropy on m Bins Given Fewer than m Samples. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Information Theory, 2004, v:50, n:9, pp:2200-2203 [Journal]
    
16. Jeremy Lewi, Robert J. Butera, Liam Paninski
    Real-time adaptive information-theoretic optimization of neurophysiology experiments. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:857-864 [Conf]
    
17. 
    Designing neurophysiology experiments to optimally constrain receptive field models along parametric submanifolds. [Citation Graph (, )][DBLP]