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Max-Planck-Institut für Experimentelle Medizin
Robert Gütig (2016).
Spiking neurons can discover predictive features by aggregate-label learning.
Science 351, aab4113-1-aab4113-14
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Gütig R (2014).
To spike, or when to spike?
Curr Opin Neurobiol. 25C, 134-139

Hillmann J, Kneib T, Koepcke L, Juárez Paz LM, Kretzberg J (2014).
Bivariate cumulative probit model for the comparison of neuronal encoding hypotheses
Biom J. 56, 23-43

Gütig R, Gollisch T, Sompolinsky H, Meister M (2013).
Computing complex visual features with retinal spike times.
PLoS One. 8, e53063-e53063

Gütig R, Sompolinsky H (2009).
Time-warp-invariant neuronal processing.
PLoS Biol. 7, e1000141-e1000141

Gütig R, Sompolinsky H (2006).
The tempotron: a neuron that learns spike timing-based decisions.
Nat Neurosci. 3, 420-428

Gütig R, Aertsen A, Rotter S (2003).
Analysis of higher-order neuronal interactions based on conditional inference.
Biol Cybern. 88, 352-359

Gütig R, Aharonov R, Rotter S, Sompolinsky H (2003).
Learning input correlations through nonlinear temporally asymmetric Hebbian plasticity.
J Neurosci. 23, 3697-3714

Gütig R, Aertsen A, Rotter S (2002).
Statistical significance of coincident spikes: count-based versus rate-based statistics.
Neural Comput. 14, 121-153

Betsch T, Plessner H, Schwieren C & Gütig R (2001).
I like it but I don't know why: A value-account approach to implicit attitude formation.
Personality and Social Psychology Bulletin 27, 242-253

Gütig R & Eberlein C (1998).
Quantum radiation from moving dielectrics in two, three, and more spatial dimensions.
Journal of Physics A 31, 6819-6838

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