Auflistung: nach Autor Pipa, Gordon


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ErscheinungsdatumTitelAutor(en)
20182D:4D and spatial abilities: From rats to humansMueller, N.; Campbell, S.; Nonaka, M.; Rost, T. M.; Pipa, G. ; Konrad, B. N.; Steiger, A.; Czisch, M.; Fernandez, G.; Dresler, M.; Genzel, L.
20172D:4D and spatial abilities: From rats to humansMüller, Nils C. J.; Campbell, Siobhan; Nonaka, Mio; Rost, Thomas; Pipa, Gordon ; Konrad, Boris N.; Steiger, Axel; Czisch, Michael; Fernández, Guillén; Dresler, Martin; Genzel, Lisa
2019A Bayesian Monte Carlo approach for predicting the spread of infectious diseasesStojanović, Olivera; Leugering, Johannes; Pipa, Gordon ; Ghozzi, Stéphane; Ullrich, Alexander
2019A Bayesian Monte Carlo approach for predicting the spread of infectious diseasesStojanovic, Olivera; Leugering, Johannes; Pipa, Gordon ; Ghozzi, Stephane; Ullrich, Alexander
2021A Minimal Model of Neural Computation with Dendritic Plateau PotentialsLeugering, Johannes; Nieters, Pascal ; Pipa, Gordon 
2011A new look at gamma? High- (> 60 Hz) gamma-band activity in cortical networks: Function, mechanisms and impairmentUhlhaas, Peter J.; Pipa, Gordon ; Neuenschwander, Sergio; Wibral, Michael; Singer, Wolf
2015A Statistical Framework to Infer Delay and Direction of Information Flow from Measurements of Complex SystemsSchumacher, Johannes; Wunderle, Thomas; Fries, Pascal; Jaekel, Frank; Pipa, Gordon 
2021A trajectory-based loss function to learn missing terms in bifurcating dynamical systemsVortmeyer-Kley, Rahel; Nieters, Pascal ; Pipa, Gordon 
2018A Unifying Framework of Synaptic and Intrinsic Plasticity in Neural PopulationsLeugering, Johannes; Pipa, Gordon 
2018Adaptive Blending Units: Trainable Activation Functions for Deep Neural NetworksSütfeld, Leon René; Brieger, Flemming; Finger, Holger; Füllhase, Sonja; Pipa, Gordon 
2020Adaptive Blending Units: Trainable Activation Functions for Deep Neural NetworksSütfeld, Leon René; Brieger, Flemming; Finger, Holger; Füllhase, Sonja; Pipa, Gordon 
2013An analytical approach to single node delay-coupled reservoir computingSchumacher, J.; Toutounji, H.; Pipa, G. 
2015An introduction to delay-coupled reservoir computingSchumacher, J.; Toutounji, H.; Pipa, G. 
2016Applicability of echo state networks to classify EEG data from a movement taskHestermeyer, L.; Pipa, G. 
2015Application of Parallel Factor Analysis (PARAFAC) to electrophysiological dataSchmitz, S. Katharina; Hasselbach, Philipp P.; Ebisch, Boris; Klein, Anja; Pipa, Gordon ; Galuske, Ralf A. W.
2011Applying the Multivariate Time-Rescaling Theorem to Neural Population ModelsGerhard, Felipe; Haslinger, Robert; Pipa, Gordon 
2015Assessing Coupling Dynamics from an Ensemble of Time SeriesGomez-Herrero, German; Wu, Wei; Rutanen, Kalle; Soriano, Miguel C.; Pipa, Gordon ; Vicente, Raul
2015Assessing Coupling Dynamics from an Ensemble of Time SeriesGómez-Herrero, Germán; Wu, Wei; Rutanen, Kalle; Soriano, Miguel C.; Pipa, Gordon ; Vicente, Raul
2010Assessing coupling dynamics from an ensemble of time seriesGómez-Herrero, Germán; Wu, Wei; Rutanen, Kalle; Soriano, Miguel C.; Pipa, Gordon ; Vicente, Raul
2017Auditory evoked potentials in lucid dreams: A dissertation summaryAppel, Kristoffer ; Pipa, Gordon