Erscheinungsdatum | Titel | Autor(en) |
2018 | A Unifying Framework of Synaptic and Intrinsic Plasticity in Neural Populations | Leugering, Johannes; Pipa, Gordon |
2018 | Adaptive Blending Units: Trainable Activation Functions for Deep Neural Networks | Sütfeld, Leon René; Brieger, Flemming; Finger, Holger; Füllhase, Sonja; Pipa, Gordon |
2020 | Adaptive Blending Units: Trainable Activation Functions for Deep Neural Networks | Sütfeld, Leon René; Brieger, Flemming; Finger, Holger; Füllhase, Sonja; Pipa, Gordon |
2013 | An analytical approach to single node delay-coupled reservoir computing | Schumacher, J.; Toutounji, H.; Pipa, G. |
2015 | An introduction to delay-coupled reservoir computing | Schumacher, J.; Toutounji, H.; Pipa, G. |
2016 | Applicability of echo state networks to classify EEG data from a movement task | Hestermeyer, L.; Pipa, G. |
2015 | Application of Parallel Factor Analysis (PARAFAC) to electrophysiological data | Schmitz, S. Katharina; Hasselbach, Philipp P.; Ebisch, Boris; Klein, Anja; Pipa, Gordon ; Galuske, Ralf A. W. |
2011 | Applying the Multivariate Time-Rescaling Theorem to Neural Population Models | Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon |
2015 | Assessing Coupling Dynamics from an Ensemble of Time Series | Gomez-Herrero, German; Wu, Wei; Rutanen, Kalle; Soriano, Miguel C.; Pipa, Gordon ; Vicente, Raul |
2015 | Assessing Coupling Dynamics from an Ensemble of Time Series | Gómez-Herrero, Germán; Wu, Wei; Rutanen, Kalle; Soriano, Miguel C.; Pipa, Gordon ; Vicente, Raul |
2010 | Assessing coupling dynamics from an ensemble of time series | Gómez-Herrero, Germán; Wu, Wei; Rutanen, Kalle; Soriano, Miguel C.; Pipa, Gordon ; Vicente, Raul |
2017 | Auditory evoked potentials in lucid dreams: A dissertation summary | Appel, Kristoffer ; Pipa, Gordon |
2016 | Automated analysis of actimetry used for the detection of disease phenotypes in sleep medicine | Leenings, R.; Glatz, C.; Boentert, M.; Heidbreder, A.; Pipa, G. ; Young, P. |
2018 | Autonomous Vehicles Require Socio-Political Acceptance-An Empirical and Philosophical Perspective on the Problem of Moral Decision Making | Bergmann, Lasse T.; Schlicht, Larissa; Meixner, Carmen; Koenig, Peter ; Pipa, Gordon ; Boshammer, Susanne ; Stephan, Achim |
2021 | Bayesian hierarchical models can infer interpretable predictions of leaf area index from heterogeneous datasets | Stojanović, Olivera; Siegmann, Bastian; Jarmer, Thomas ; Pipa, Gordon ; Leugering, Johannes |
2021 | Biologically Inspired Deep Learning Model for Efficient Foveal-Peripheral Vision | Lukanov, Hristofor; Koenig, Peter ; Pipa, Gordon |
2019 | Bistable Perception in Conceptor Networks | Meyer zu Driehausen, F.; Busche, R.; Leugering, J.; Pipa, G. |
2017 | Classifying bio-inspired model of point-light human motion using Echo State networks | Tanisaro, P.; Lehman, C.; Sütfeld, L.; Pipa, G. ; Heidemann, G. |
2019 | Combining Deep Learning and (Structural) Feature-Based Classification Methods for Copyright-Protected PDF Documents | Garita Figueiredo, R.; Kühnberger, K.-U. ; Pipa, G. ; Thelen, T. |
2012 | Context Matters: The Illusive Simplicity of Macaque V1 Receptive Fields | Haslinger, Robert; Pipa, Gordon ; Lima, Bruss; Singer, Wolf; Brown, Emery N.; Neuenschwander, Sergio |