Felipe Gerhard - Publications

École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland 
computational neuroscience

13 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2017 Gerhard F, Deger M, Truccolo W. On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs. Plos Computational Biology. 13: e1005390. PMID 28234899 DOI: 10.1371/Journal.Pcbi.1005390  0.566
2013 Lütcke H, Gerhard F, Zenke F, Gerstner W, Helmchen F. Inference of neuronal network spike dynamics and topology from calcium imaging data. Frontiers in Neural Circuits. 7: 201. PMID 24399936 DOI: 10.3389/Fncir.2013.00201  0.678
2013 Gerhard F, Kispersky T, Gutierrez GJ, Marder E, Kramer M, Eden U. Successful reconstruction of a physiological circuit with known connectivity from spiking activity alone. Plos Computational Biology. 9: e1003138. PMID 23874181 DOI: 10.1371/Journal.Pcbi.1003138  0.552
2013 Gerhard F, Kispersky T, Gutierrez GJ, Marder E, Kramer M, Eden U. Successful prediction of a physiological circuit with known connectivity from spiking activity alone Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P118  0.581
2012 Gerhard F, Szegletes L. Spline- and wavelet-based models of neural activity in response to natural visual stimulation. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 2012: 4611-4. PMID 23366955 DOI: 10.1109/EMBC.2012.6346994  0.419
2011 Naud R, Gerhard F, Mensi S, Gerstner W. Improved similarity measures for small sets of spike trains. Neural Computation. 23: 3016-69. PMID 21919785 DOI: 10.3389/Conf.Fncom.2010.51.00102  0.678
2011 Gerhard F, Haslinger R, Pipa G. Applying the multivariate time-rescaling theorem to neural population models. Neural Computation. 23: 1452-83. PMID 21395436 DOI: 10.1162/Neco_A_00126  0.698
2011 Gerhard F, Pipa G, Lima B, Neuenschwander S, Gerstner W. Extraction of Network Topology From Multi-Electrode Recordings: Is there a Small-World Effect? Frontiers in Computational Neuroscience. 5: 4. PMID 21344015 DOI: 10.3389/Fncom.2011.00004  0.701
2011 Gerhard F, Gerstner W. Efficient modeling of neural activity using coupled renewal processes Bmc Neuroscience. 12. DOI: 10.1186/1471-2202-12-S1-P123  0.688
2010 Gerhard F, Haslinger R, Pipa G. Goodness-of-fit tests for neural population models: the multivariate time-rescaling theorem Bmc Neuroscience. 11. DOI: 10.1186/1471-2202-11-S1-P46  0.707
2010 Gerhard F, Gerstner W. Rescaling, thinning or complementing? on goodness-of-fit procedures for point process models and Generalized Linear Models Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010 0.504
2009 Gerhard F, Schiemann J, Roeper J, Schneider G. A simple Hidden Markov Model for midbrain dopaminergic neurons Bmc Neuroscience. 10. DOI: 10.1186/1471-2202-10-S1-P235  0.619
2009 Gerhard F, Savin C, Triesch J. A robust biologically plausible implementation of ICA-like learning Esann 2009 Proceedings, 17th European Symposium On Artificial Neural Networks - Advances in Computational Intelligence and Learning. 147-152.  0.43
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